Case3:15-cv-02579 Document1 Filed06/10/15 Page1 of 8 1 2 3 4 5 6 7 8 9 10 KALPANA SRINIVASAN (237460) ksrinivasan@susmangodfrey.com OLEG ELKHUNOVICH (269238) oelkhunovich@susmangodfrey.com SUSMAN GODFREY L.L.P. 1901 Avenue of the Stars, Suite 950 Los Angeles, California 90067-6029 [Tel.] (310) 789-3100 [Fax] (310) 789-3150 MAX L. TRIBBLE, JR. (Pending Admission Pro Hac Vice) mtribble@susmangodfrey.com SUSMAN GODFREY L.L.P. 1000 Louisiana, Suite 5100 Houston, Texas 77002-5096 [Tel.] (713) 651-9366 [Fax] (713) 654-6666 Attorneys for Plaintiffs AliphCom d/b/a Jawbone and BodyMedia, Inc. (Additional Counsel for Plaintiffs listed below signature line) 11 12 13 UNITED STATES DISTRICT COURT 14 NORTHERN DISTRICT OF CALIFORNIA 15 16 ALIPHCOM D/B/A JAWBONE and BODYMEDIA, INC. 17 Plaintiffs, 18 v. 19 FITBIT, INC. Case No: 3:15-cv-2579 COMPLAINT FOR PATENT INFRINGEMENT JURY TRIAL DEMANDED 20 Defendant. 21 22 23 24 25 26 27 28 COMPLAINT FOR PATENT INFRINGEMENT 3740183v1/014661 Case3:15-cv-02579 Document1 Filed06/10/15 Page2 of 8 1 Plaintiffs AliphCom d/b/a Jawbone and BodyMedia, Inc. (collectively, “Plaintiffs” or 2 “Jawbone”), by their undersigned attorneys, for their complaint against Fitbit, Inc. (“Fitbit”), 3 hereby allege the following: 4 1. This is an action for patent infringement arising under the patent laws of the 5 United States, Title 35 of the United States Code.1 Jawbone seeks damages and injunctive relief 6 for infringement of its patents by Fitbit’s wearable fitness tracker devices. 7 8 2. AliphCom is a corporation organized and existing under the laws of California with its principal place of business located in San Francisco, California. 9 3. BodyMedia, Inc. is a corporation organized and existing under the laws of 10 Delaware with its principal place of business located in Pittsburgh, Pennsylvania. BodyMedia is 11 a wholly owned subsidiary of AliphCom. 12 4. Plaintiffs are informed and believe, and on that basis allege, that Defendant Fitbit 13 is a corporation organized and existing under the laws of Delaware with its headquarters at 405 14 Howard Street, San Francisco, CA 94105. Fitbit transacts substantial business, either directly or 15 through its agents, on an ongoing basis in this judicial district and elsewhere in the United States. 16 JURISDICTION AND VENUE 17 18 5. This Court has subject matter jurisdiction pursuant to 28 U.S.C. §§ 1331 and 1338(a). 19 6. This Court has personal jurisdiction over Defendant because Defendant is located 20 in this District, has committed acts of infringement in violation of 35 U.S.C. § 271, and has 21 placed infringing products into the stream of commerce, through an established distribution 22 channel, with the knowledge and/or understanding that such products are used and sold in this 23 District. These acts cause injury to Plaintiffs within the District. Defendant derives revenue from 24 the sale of infringing products distributed within the District, expects or should reasonably expect 25 1 26 27 28 AliphCom and BodyMedia intend to file a complaint requesting the International Trade Commission (ITC) to commence an investigation pursuant to Section 337 of the Tariff Act of 1930, 19 U.S.C. § 1337, of Fitbit’s unlawful importation into the United States, sale for importation into the United States, and sale within the United States after importation of products that infringe AliphCom and BodyMedia’s patents. The ITC complaint will include some or all of the patents and accused products asserted in this district court action. COMPLAINT FOR PATENT INFRINGEMENT 720498v1/014661 1 Case3:15-cv-02579 Document1 Filed06/10/15 Page3 of 8 1 transactions to have consequences within the District, and derives substantial revenue from 2 interstate and international commerce. 3 7. Venue is proper in this Federal District pursuant to 28 U.S.C. §§ 1391(b)-(c) and 4 1400(b) in that Defendant has a regular and established place of business in this District, a 5 substantial part of the events giving rise to the claim occurred in this District, and Defendant has 6 committed acts of infringement in this district. 7 8 BACKGROUND 8. Jawbone is a world leader in consumer technology and wearable devices with 9 hundreds of patents that have been granted or are pending related to Jawbone’s ecosystem and 10 wearable technology manufacturing processes. In the field of wearable technology, Jawbone’s 11 UP® system in connection with its UP Move, UP2 and UP3 trackers collect and provide 12 personalized data about how consumers sleep, move and eat. The UP Platform also includes apps 13 and services that integrate with UP devices to offer new, customized experiences. 14 15 16 9. In April 2013, AliphCom acquired BodyMedia for over $100 million and obtained the rights to BodyMedia’s expansive patent portfolio in the field of wearable technology. 10. BodyMedia helped to pioneer the development of wearable body monitors that 17 collect physiological data for use in improving health, wellness and fitness. Founded in 1999, 18 BodyMedia patented widely in the field of wearable technology. 19 11. Together, BodyMedia and Jawbone have almost three decades worth of 20 technology, science and intellectual property around wearable trackers that allow consumers to 21 measure their activity and set wellness goals. 22 12. Jawbone has invested heavily in its wearable technology business. In just the last 23 two years, Jawbone has spent well over a $100 million in research and development related to its 24 wearable devices along with the technology and underlying systems that support them. 25 13. Jawbone employs over 400 people, spread across Jawbone’s San Francisco, 26 Sunnyvale, Pittsburgh, Seattle, and New York facilities as well as overseas. 27 operations include BodyMedia employees and research operations. 28 COMPLAINT FOR PATENT INFRINGEMENT 720498v1/014661 2 Jawbone’s Case3:15-cv-02579 Document1 Filed06/10/15 Page4 of 8 1 14. Fitbit competes directly with Jawbone in the market for wearable fitness and 2 activity trackers through its product line, most notably the Zip, One, Flex, Charge, Charge HR, 3 Surge. These trackers – which make up virtually all of Fitbit’s wearable technology line – 4 infringe one or more of the Jawbone patents. 5 COUNT 1 – INFRINGEMENT OF U.S. PATENT NO. 8,446,275 6 15. On May 21, 2013, the United States Patent and Trademark Office issued United 7 States Patent No. 8,446,275 (“the ’275 patent”) for an invention entitled “General Health And 8 Wellness Management Method And Apparatus For A Wellness Application Using Data From A 9 Data-Capable Band.” AliphCom is the assignee and owner of the ’275 patent and holds all rights, 10 title and interests in the ‘275 patent, including the right to sue for and recover all past, present and 11 future damages for infringement. A true and correct copy of the ’275 patent is attached as Exhibit 12 A. 13 16. Fitbit has infringed and continues to infringe one or more claims of the ’275 patent 14 by its making, manufacture, use, sale, importation, or offer for sale of its wearable fitness tracker 15 devices, including but not limited to the following: Zip, One, Flex, Charge, Charge HR, Surge, 16 and reasonably similar products. 17 18 19 17. Fitbit is liable for its infringement of the ’275 patent pursuant to 35 U.S.C. § 271(a), (b), and (c). 18. Fitbit knowingly induces others to perform steps that infringe claims of the ’275 20 patent. Fitbit’s inducement of infringement includes, but is not limited to: (i) knowledge of the 21 ’275 patent; (ii) intent to induce direct infringement of the ’275 patent; (iii) knowingly aiding and 22 abetting infringement at least by providing and encouraging the use of the Fitbit App and/or Fitbit 23 Dashboard, as well as by providing instruction manuals, online websites including tutorials and 24 frequently asked questions, and other directions that instruct the purchaser or user of an accused 25 device to use that device in a manner that infringes certain claims of the ’275 patent; and (iv) 26 actual or constructive knowledge that their actions induce infringement. 27 28 19. Fitbit is also liable for contributory infringement because it offers to sell or sells within the United States or imports into the United States wearable fitness tracker devices that COMPLAINT FOR PATENT INFRINGEMENT 720498v1/014661 3 Case3:15-cv-02579 Document1 Filed06/10/15 Page5 of 8 1 constitute a component of a patented combination and a material part of the invention claimed by 2 the ’275 patent, knowing the same to be especially made or especially adapted for use in an 3 infringement of such patent, which wearable fitness tracker devices are not a staple article or 4 commodity of commerce suitable for substantial noninfringing use. 5 20. Fitbit’s acts of infringement have damaged Plaintiffs, and Plaintiffs are entitled to 6 recover from Fitbit the damages they have sustained as a result of Fitbit’s wrongful acts in an 7 amount subject to proof at trial. Fitbit’s infringement of Plaintiffs’ rights under the ’275 patent 8 will continue to damage Plaintiffs, causing irreparable harm for which there is no adequate 9 remedy at law, unless enjoined by this Court. 10 11 COUNT 2 – INFRINGEMENT OF U.S. PATENT NO. 8,073,707 21. On December 6, 2011, the United States Patent and Trademark Office issued 12 United States Patent No. 8,073,707 (“the ’707 patent”) for an invention entitled “System For 13 Detecting, Monitoring, And Reporting An Individual’s Physiological Or Contextual Status.” 14 BodyMedia is the assignee and owner of the ’707 patent and holds all rights, title and interests in 15 the ‘707 patent, including the right to sue for and recover all past, present and future damages for 16 infringement. A true and correct copy of the ’707 patent is attached as Exhibit B. 17 22. Fitbit has infringed and continues to infringe one or more claims of the ’707 patent 18 by its making, manufacture, use, sale, importation, or offer for sale of its wearable fitness tracker 19 devices, including but not limited to the following: Charge HR, Surge, Aria, and reasonably 20 similar products. 21 23. 22 271(a), (b), and (c). 23 24. Fitbit is liable for its infringement of the ’707 patent pursuant to 35 U.S.C. § Fitbit knowingly induces others to perform steps that infringe claims of the ’707 24 patent. Fitbit’s inducement of infringement includes, but is not limited to: (i) knowledge of the 25 ’707 patent; (ii) intent to induce direct infringement of the ’707 patent; (iii) knowingly aiding and 26 abetting infringement at least by providing and encouraging the use of the Fitbit App and/or Fitbit 27 Dashboard, as well as by providing instruction manuals, online websites including tutorials and 28 frequently asked questions, and other directions that instruct the purchaser or user of an accused COMPLAINT FOR PATENT INFRINGEMENT 720498v1/014661 4 Case3:15-cv-02579 Document1 Filed06/10/15 Page6 of 8 1 device to use that device in a manner that infringes certain claims of the ’707 patent; and (iv) 2 actual or constructive knowledge that their actions induce infringement. 3 25. Fitbit is also liable for contributory infringement because it offers to sell or sells 4 within the United States or imports into the United States fitness tracker devices that constitute a 5 component of a patented combination and a material part of the invention claimed by the ’707 6 patent, knowing the same to be especially made or especially adapted for use in an infringement 7 of such patent, which fitness tracker devices are not a staple article or commodity of commerce 8 suitable for substantial noninfringing use. 9 26. Fitbit’s acts of infringement have damaged Plaintiffs, and Plaintiffs are entitled to 10 recover from Fitbit the damages they have sustained as a result of Fitbit’s wrongful acts in an 11 amount subject to proof at trial. Fitbit’s infringement of Plaintiffs’ rights under the ’707 patent 12 will continue to damage Plaintiffs, causing irreparable harm for which there is no adequate 13 remedy at law, unless enjoined by this Court. 14 15 COUNT 3 – INFRINGEMENT OF U.S. PATENT NO. 8,398,546 27. On March 19, 2013, the United States Patent and Trademark Office issued United 16 States Patent No. 8,398,546 (“the ’546 patent”) for an invention entitled “System For Monitoring 17 And Managing Body Weight And Other Physiological Conditions Including Iterative And 18 Personalized Planning, Intervention And Reporting Capability.” BodyMedia is the assignee and 19 owner of the ’546 patent and holds all rights, title and interests in the ‘546 patent, including the 20 right to sue for and recover all past, present and future damages for infringement. A true and 21 correct copy of the ’546 patent is attached as Exhibit C. 22 28. Fitbit has infringed and continues to infringe one or more claims of the ’546 patent 23 by its making, manufacture, use, sale, importation, or offer for sale of its wearable fitness tracker 24 devices, including but not limited to the following: 25 reasonably similar products. 26 29. 27 271(a), (b), and (c). Fitbit is liable for its infringement of the ’546 patent pursuant to 35 U.S.C. § 28 COMPLAINT FOR PATENT INFRINGEMENT 720498v1/014661 One, Charge, Charge HR, Surge, and 5 Case3:15-cv-02579 Document1 Filed06/10/15 Page7 of 8 1 30. Fitbit knowingly induces others to perform steps that infringe claims of the ’546 2 patent. Fitbit’s inducement of infringement includes, but is not limited to: (i) knowledge of the 3 ’546 patent; (ii) intent to induce direct infringement of the ’546 patent; (iii) knowingly aiding and 4 abetting infringement at least by providing and encouraging the use of the Fitbit App and/or Fitbit 5 Dashboard, as well as by providing instruction manuals, online websites including tutorials and 6 frequently asked questions, and other directions that instruct the purchaser or user of an accused 7 device to use that device in a manner that infringes certain claims of the ’546 patent; and (iv) 8 actual or constructive knowledge that their actions induce infringement. 9 31. Fitbit is also liable for contributory infringement because it offers to sell or sells 10 within the United States or imports into the United States wearable fitness tracker devices that 11 constitute a component of a patented combination and a material part of the invention claimed by 12 the ’546 patent, knowing the same to be especially made or especially adapted for use in an 13 infringement of such patent, which wearable fitness tracker devices are not a staple article or 14 commodity of commerce suitable for substantial noninfringing use. 15 32. Fitbit’s acts of infringement have damaged Plaintiffs, and Plaintiffs are entitled to 16 recover from Fitbit the damages they have sustained as a result of Fitbit’s wrongful acts in an 17 amount subject to proof at trial. Fitbit’s infringement of Plaintiffs’ rights under the ’546 patent 18 will continue to damage Plaintiffs, causing irreparable harm for which there is no adequate 19 remedy at law, unless enjoined by this Court. 20 JURY DEMAND 21 22 33. Pursuant to Rule 38(b) of the Federal Rules of Civil Procedure, Plaintiffs respectfully requests a trial by jury on all issues. 23 PRAYER FOR RELIEF 24 WHEREFORE, Plaintiffs request entry of judgment in their favor and against Fitbit as 25 follows: 26 a. Declaring that Defendant has infringed the ’275,’707 and ’546 patents; 27 28 COMPLAINT FOR PATENT INFRINGEMENT 720498v1/014661 6 Case3:15-cv-02579 Document1 Filed06/10/15 Page8 of 8 1 b. Awarding compensatory damages arising out of Defendant’s infringement of the 2 ’275,’707 and ’546 patents to Plaintiffs together with prejudgment and post-judgment 3 interest, in an amount according to proof; 4 c. Permanently enjoining Defendant and its respective officers, agents, employees, and 5 those acting in privity with them from the make, manufacture, use, sale, importation, 6 or offer for sale of products that infringe, including by contributory infringement or 7 induced infringement, the ’275,’707 and ’546 patents; 8 d. 9 10 Awarding attorney’s fees pursuant to 35 U.S.C. § 285 or as otherwise permitted by law; and e. Awarding such other costs and further relief as the Court may deem just and proper. 11 12 Dated: June 10, 2015 13 14 KALPANA SRINIVASAN MAX L. TRIBBLE, JR. (Pending Pro Hac Vice) OLEG ELKHUNOVICH SUSMAN GODFREY LLP GENEVIEVE VOSE WALLACE (Pending Pro Hac Vice ) gwallace@susmangodfrey.com FLOYD G. SHORT (Pending Pro Hac Vice ) fshort@susmangodfrey.com SUSMAN GODFREY L.L.P. 1201 Third Avenue, Suite 3800 Seattle, Washington 98101-3000 Telephone: (206) 516-3880 Facsimile: (206) 516-3883 15 16 17 18 19 20 By: 21 /s/ Kalpana Srinivasan Kalpana Srinivasan Attorneys for Plaintiffs AliphCom d/b/a Jawbone and BodyMedia, Inc. 22 23 24 25 26 27 28 COMPLAINT FOR PATENT INFRINGEMENT 720498v1/014661 7 Documentl-l Filed06/10/15 Pagel of 64 Exhibit A Case3:15-cv-02579 Document1-1 Filed06/10/15 Page2 of 64 US008446275B2 (12) (54) (75) (73) (*) United States Patent (io) Patent No.: Utter, II (45) GENERAL HEALTH AND WELLNESS MANAGEMENT METHOD AND APPARATUS FOR A WELLNESS APPLICATION USING DATA FROM A DATA-CAPABLE BAND Inventor: U.S. PATENT DOCUMENTS (22) Filed: FOREIGN PATENT DOCUMENTS EP EP OTHER PUBLICATIONS (Continued) Dec. 13, 2012 Primary Examiner — Toan N Pham (74) Attorney, Agent, or Firm — Kokka & Backus, PC Related U.S. Application Data (51) Continuation-in-part of application No. 13/433,204, filed on Mar. 28, 2012, which is a continuation-in-part of application No. 13/181,495, filed on Jul. 12, 2011, which is a continuation-in-part of application No. 13/180,000, filed on Jul. 11,2011, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,416, filed on Jun. 11, 2011, which is a continuation-in-part of application No. 13/158,372, filed on Jun. 10,2011, said application No. 13/181,495 is a continuation-in-part of application No. (Continued) (52) (58) General health and wellness management techniques and devices are configured for use with a data-capable personal worn or carried device. In one embodiment, a methodreceiv­ ing data representing a profile upon which a target score is established based on one or more health-related activities, and acquiring data representing one or more subsets of acquired parameters based on, for example, one or more sensors disposed in a wearable computing device. The method can include determining data representing values for the one or more subsets of the acquired parameters based on reference values for the parameters set forth in the profile and calculating at a first processor a score based on data repre­ senting the values. The score represents an attained portion of the one or more health-related activities. In some cases, the method includes causing presentation of a representation of the score relative to the target score. (2006.01) U.S. CI. USPC 340/539.12; 340/573.1; 600/300; 600/301; 482/9 Field of Classification Search 340/539.12,573.1,691.6,693.5, USPC 340/3.1, 3.31; 600/509, 300, 301; 482/8, 482/9, 900; 128/905, 920 See application file for complete search history. f ABSTRACT (57) Int. CI. G08B 1/08 3/2006 9/2006 U.S. Appl. No. 61/516,479, Fish et al. Prior Publication Data US 2012/0313776 Al (63) 1639939 1702560 (Continued) Apr. 23, 2012 (65) 11/1988 Ehlert et al. 4/1989 Hargrove et al. (Continued) Subject to any disclaimer, the term of this patent is extended or adjusted under 35 U.S.C. 154(b) by 0 days. Appl.No.: 13/454,040 May 21, 2013 References Cited 4,788,627 A 4,819,860 A Max Everett Utter, II, San Francisco, CA (US) (21) US 8,446,275 B2 Date of Patent: (56) Assignee: AliphCom, San Francisco, CA (US) Notice: Illllllllllllllllllll 19 Claims, 32 Drawing Sheets DsiV." tvft \ ^ : / \ 'v'Vi' iS* :::::: & N, X S '4 •s N/"ICS Case3:15-cv-02579 Document1-1 Filed06/10/15 Page3 of 64 US 8,446,275 B2 Page 2 Related U.S. Application Data 13/180,320, filed on Jul. 11,2011, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, said application No. 13/181,495isa continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, said application No. 13/181,495isa continuation-in-part of application No. 13/158,372, said application No. 13/433,204 is a continuation-in-part of application No. 13/180,320, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/361,919, filed on Jan. 30, 2012, which is a continuation of application No. 13/181,495, said application No. 13/433,204 is a continuation-in-part of application No. 13/180,000, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, said application No. 13/181,495isa continuation-in-part of application No. 13/180,320, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, said application No. 13/361,919 is a continuation of application No. 13/181,511, filed on Jul. 12, 2011, said application No. 13/433,204 is a continuation-in-part of application No. 13/180,000, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, said application No. 13/181,511 is a continuation-in-part of application No. 13/180,320, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/181,511, which is a continuation-in-part of application No. 13/180,000, which is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, said application No. 13/181,511 is a continuation-in-part of application No. 13/180,320, said application No. 13/433,204 is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/433,208, filed on Mar. 28, 2012, which is a continuation-in-part of application No. 13/181,495, which is a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. and 13/180,320, a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/361,919, which is a continuation of application No. 13/181,495, and a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation of application No. 13/181,511, and a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/181,511, and a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/433,213, filed on Mar. 28, 2012, which is a continuation-in-part of application No. 13/181,495, which is a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/361,919, which is a continuation of application No. 13/181,495, and a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, Case3:15-cv-02579 Document1-1 Filed06/10/15 Page4 of 64 US 8,446,275 B2 Page 3 which is a continuation-in-part of application No. 13/158,372, and a continuation of application No. 13/181,511, and a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/181,511, and a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No.13/361,919, which is a continuation of application No. 13/181,495, and a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation of application No.13/181,511, and a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, which is a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/181,511, and a continuation-in-part of application No. 13/180,000, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372, and a continuation-in-part of application No. 13/180,320, and a continuation-in-part of application No. 13/158,416, which is a continuation-in-part of application No. 13/158,372. 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I PI t f :§ I I t f ® ^>.1$ -i K ^§ § I lllll f & £ I C> f £» • $ f"** 11^ <• * •X « 'MB •'•'•' i I mt ''iim. VA2 nfl :r 1 •; * K ' '' •oaaoaBc jMk -QUMUL 111 m4 J 5 rm F I G . 11 s ? «/« mi ...xf V-'%i ms BAT 6l Bfm Case3:15-cv-02579 Document1-1 Filed06/10/15 Page23 of 64 U.S. Patent May 21, 2013 US 8,446,275 B2 Sheet 16 of 32 iaoo •$. 1204A 1218 ^ 1mm II \ hm ^nm 1208 f .&*»&»* lis&ab J2iQ : i *.!;< Ian. M2 tJK fitritti ind nyirllon, .ivny i piigririi. moimiioa i iKificsfiiit i -t-i a vLfeJ^. I I My Team Summary iaas jW* I'M. ivi* >: Case3:15-cv-02579 Document1-1 Filed06/10/15 Page24 of 64 U.S. Patent May 21, 2013 US 8,446,275 B2 Sheet 17 of 32 1230 12048 1202^ HSmiWriim iat« PiMal Move m ti¥$ Yw: Mm ! i sm. mm 1242 i FIG, 12! Case3:15-cv-02579 Document1-1 Filed06/10/15 Page25 of 64 U.S. Patent May 21, 2013 US 8,446,275 B2 Sheet 18 of 32 1250 1204* 1202, 1218 HSisinp Vm .1254 Statistics Flfiport mm i242A MM. 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Case3:15-cv-02579 Document1-1 Filed06/10/15 Page27 of 64 U.S. Patent May 21, 2013 US 8,446,275 B2 Sheet 20 of 32 1270 12041;; 1216 * 1202. itrti: Saarcri, mcommenciaiions. *^ y-i JAlA S2M MM $ippterriiri! of tli« 1 12mA &/ L 'S 1 } 12400 Best Folsowers and Weight loss ^ ^ 1 FIG, 12E Case3:15-cv-02579 Document1-1 Filed06/10/15 Page28 of 64 U.S. Patent May 21, 2013 US 8,446,275 B2 Sheet 21 of 32 1280 1204F Eat Find a program; m2 Um Smmb* Mm j i i i I 1. 1 SK 1 0/ Pmduet Hescare n .I2S0 1216 mz Case3:15-cv-02579 Document1-1 Filed06/10/15 Page29 of 64 U.S. Patent May 21, 2013 US 8,446,275 B2 Sheet 22 of 32 1300 1314 1 I Slomge Dmkm I I 131?® Iftput Device 1310 4 I ••••>-• .13.18 1302 Pfocmmr Interface 1304 Gumor 1318 FIG, 13 1320 o Case3:15-cv-02579 Document1-1 Filed06/10/15 Page30 of 64 U.S. Patent May 21, 2013 US 8,446,275 B2 Sheet 23 of 32 nm H Erpm* 141g r Acuity l^anapr 1432 1430 Clernsml Heallh/Weloess MulriSsn 1434 Status Manager MM ^lansipr 1436 Hapic Engirt© MM S» Deploy E^gmo MM r MM OMvW&Qfi 1:420 Score Generator mz Emphssss 1424 AM '-wl470 14?2' CMpulfS} Case3:15-cv-02579 Document1-1 Filed06/10/15 Page31 of 64 U.S. Patent May 21,2013 US 8,446,275 B2 Sheet 24 of 32 1800 Aggrtp&on £«§&# im MM MMl Oemsral - *m H«alts/W«!fewsis Mansge? 1S2S*~%j 0^»C: G®mm yanagtr lS3la ' ieMMMMMMMMMMW ! »w»: •»«• m !Wmmmsmmmmm il $8mp ll Maiiansr i Acstivily temgtr m«?tal Manager im* 1537 tm IMMMMMM NMM0000000M04 mi* '•WV. .WVV VVW ?i MAS » - Ommmm Wodute MM Scorn B%mmm : SKN •x E -Sy Si jMMt A/S/N Bmm BiimiMC'f ^ Social Manager i&gs i Ji mm! 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Empr^asis m Contexl Scom Qwmmr WW«««»8»»889888 888 8 88 »88 8 88 »88iW : Case3:15-cv-02579 Document1-1 Filed06/10/15 Page32 of 64 U.S. Patent May 21, 2013 Sheet 25 of 32 1S5CI Sian 16i2 mvi wtMmm of om or m&re •:• -v" •••••* Calculate to pmmiM&m A§greg..»y.'rt*i*^**''^^ umA, C \ \ fvVWM I/ % I %m2^f V i 1600 (S. 1808^ \// PFff Vi ^ OT MA >MA A P«met$r« •.'.'.'.•.•.•.'.'.•.•.'.•.'.•.•f / m* I ' fPEyiS ] Paf»m©^r$:i 1620 fww"**" 1846 1632 Nufetton ^ igZ2**f*f i . r.ijii i rir "i'* *'"'** *' j»ii iriri"r; "' * id SoeW Marm^ ««««<<«««0<<<<<<<<0<1<1<1<1<1 u UII mi"1""** £nvror?m&Ht3) ^srsagsr IMZ JU^S —* Gsnfefai Comaxt Haail8VW^lto6BS® Score ivtestjef' (3^f>@?al©r iiai OMM iM2 MMi idjgp fid. 18A to Hspite amdtof ^ Dismay Case3:15-cv-02579 Document1-1 Filed06/10/15 Page34 of 64 U.S. Patent May 21, 2013 nm y stajt Reoei ve m or mof!>• JUL! vaK- * ^ w*' 1680 :«tt 5» •>« >» «. 1684 "%• ..r> •y^' I I // 1 ^ 1 II ••••v -j * »s w ";v**> I , •5Vv -VM^. 18i6 FRI "'^Sv ... A*X*»>»»>»»>»»>>»»>>>>* "Ns v-»»»»»»>!-^->»»»»»>; m twm ••pal: Am;;;sgft Ssm ihis wm&ftmil with I •^. 1, 4,0?' 7 ¥iB, 16C 1690 1SS2 •$••;• •i *.•"i* v •:• T"// y[ ..>•••• ^W.'.V.W.WiW.^g^WW.V.*. yr^* ...••*'•* < / ** I ? 5 J ^ "ffei i:? -"r'f;-: I :>• RM ^ €>. I I L 1694 i 8*1 S -••'V. ••'><.. .. *>Vv. I ••>.x -Sss; v-<.. " dfesn. i Case3:15-cv-02579 Document1-1 Filed06/10/15 Page36 of 64 U.S. Patent May 21, 2013 US 8,446,275 B2 Sheet 29 of 32 1?«? ^ .. i^ftysse®} \ Pwmwsws 1 Vim jf % Pmwrzmm m4 f .. V ^ xm 1222 . 0«in«Tal rt&allh/W®i«ts© Manager Soessi Psrsm^rs Psrasri^sfs ^Gti WW** 8*Hw Date im-e^ace 6>S*S( i.mi. isas 1703-v Healili/Weinass Awiava! Data CtMroiter im 1113 y**-^ Ctn&td'^oiim i?m ZktmrM HJ W fMisfam# Pmil^s) r- 1?QS 170? - "Vvi #»•' Proll® G^^femtor Pfolte s} WOK mm 1?f0 1708 i?ao "v* To Sc«fe CimmaiQ? m®?m Om or mom Maoagers FIO.ITA Case3:15-cv-02579 Document1-1 Filed06/10/15 Page37 of 64 U.S. Patent May 21,2013 Sheet 30 of 32 US 8,446,275 B2 rm :$IM 1752" mam pamrmtms mm AcquSW^iWiiwia^xHiEdwlh mvi vs^ffn^ss of om or mom mm 1?5< i7§$~w. Caioilafe ssomCs) mfetive to wtomtm pammetsm Adjast one or mom scorns h&m% 1ors om or mom ihs scquirtd I ijamm^fers kfenf% chamcfefMcs o f heaih ami 1 782'~M 1760 F^db^±: V to bQ mwMM for improved indicBtrng Imprmgd btsilh and w@fc©$8 N MocMatedeMnMMOfl 1784 -~H • 1708«~^' 1?79~*? i7?a^ "V EfXl FIG, ITS Monitor i» ototoin more aoqwed Case3:15-cv-02579 Document1-1 Filed06/10/15 Page38 of 64 U.S. Patent May 21, 2013 Wakefuin-sss Slafe 1S.10 10-0 Sleep 1»1i? I felartager 1S30 SSate Steep State •v SmaMa^ ttm Nutstfe Manager 1534 US 8,446,275 B2 Sheet 31 of 32 I timch Dinner I imi 1808 M rA iao4 1 I i ^ V»: l I I ->» fsme na ISA Wsy^ulness .>»>>>>>» SMe 1820 1B02 18^2 { l^^ii Sleep Blmp ygnsgsf Slats JSO Run i^yhy^yhyhy> AeftrSty ^ 1814 Wanagar m2 \ i L I Step S«t0 I laia 1 walk <1816 i I \ I i ^T\ ^vL-^iv^ Hf* I -"Sv-i. .J S## I\ I FIG. 168 I time Case3:15-cv-02579 Document1-1 Filed06/10/15 Page39 of 64 U.S. Patent Sheet 32 of 32 May 21,2013 US 8,446,275 B2 1632 sr* im MM AotMty I !. S I 1830 \ '18^6i Wf>d < - .r * "wasr t 'lunch" Managef IM? w* MiM) <• iasg I « "Fr^d" r i igg© Acivily / iXi UiS lamtw • ^ tag? PmmMty Sodsl Manager ^ ,>j L^1S82 li f§ 1S2 ActMfy MM jAc^v%sL i ten® Case3:15-cv-02579 Document1-1 Filed06/10/15 Page40 of 64 US 8,446,275 B2 1 2 GENERAL HEALTH AND WELLNESS MANAGEMENT METHOD AND APPARATUS FOR A WELLNESS APPLICATION USING DATA FROM A DATA-CAPABLE BAND of prior U.S. patent application Ser. No. 13/158,416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, and also is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,416, filed Jun. 11, 2011, which is a continuationin-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, and is also a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011; U.S. non-provisional patent application Ser. No. 13/433,204 is also a continuation-in-part of U.S. Nonprovisional patent application Ser. No. 13/361,919, filed Jan. 30, 2012, which is a continuation of U.S. Nonprovisional patent application Ser. No. 13/181,495 filed Jul. 12, 2011, which claims the benefit of U.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provi­ sional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filed Jun. 11, 2011 and, U.S. Nonprovisional patent application Ser. No. 13/361,919 is a continuation-in-part ofU.S. patent application Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional PatentApplicationNo. 61/495, 995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,996 filed Jun. 11, 2011 and U.S. Nonprovisional patent application Ser. No. 13/361, 919 is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuationin-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. Nonprovisional patent application Ser. No. 13/181,495 filed Jul. 12, 2011 is also a continuation-inpart ofU.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filed. Jun. 11,2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. Nonprovisional patent application Ser. No. 13/361,919 is also a continuation ofU.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Applica­ tion No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filed Jun. 11,2011,U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filed Jun. 11,2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011 is also a continuation-inpart ofU.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 5 CROSS-REFERENCE TO RELATED APPLICATIONS THIS application is a continuation-in-part of U.S. nonprovisional patent application 13/433,204, filed Mar. 28, 2012, which is a continuation-in-part of U.S. non-provisional patent application Ser. No. of 13/181,495, filed Jul. 12, 2011, which is a continuation-in-part of prior U.S. patent applicationSer.No. 13/180,000, filed Jul. 11,2011, which claims the benefit of U.S. Provisional Patent Application No. 61/495, 995, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, U.S. Provi­ sional Patent Application No. 61/495,996, filed Jun. 11,2011, and U.S. patent application Ser. No. 13/180,000 is a continuation-in-part of prior U.S. patent application Ser. No. 13/158, 416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, and U.S. patent application Ser. No. 13/181,495 claims the benefit ofU.S. Provisional PatentApplicationNo. 61/495,995, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,997, filed Jun. 11,2011, and U.S. Provisional PatentApplicationNo. 61/495,996, filed Jun. 11, 2011; U.S. patent application Ser. No. 13/181,495 is also a continuation-in-part of prior U.S. patent application Ser. No. 13/180,320, filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495, 995, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994, filed Jun. 11, 2011, U.S. Provisional Patent ApplicationNo. 61/495,997, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,996, filed Jun. 11,2011, and U.S. patent application Ser. No. 13/180,320 is a continu­ ation-in-part of prior U.S. patent application Ser. No. 13/158, 416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994, filed Jun. 11,2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996, filed Jun. 11, 2011; U.S. patent application Ser. No. 13/181,495 is also a continuation-in-part of prior U.S. patent application Ser. No. 13/158,416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,495 is also a continuation-in-part of prior U.S. patent application Ser. No.13/158,372, filed Jun. 10, 2011; U.S. non-provisional patent application Ser. No. 13/433,204 claims the benefit ofU.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994, filed Jun. 11,2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, and U.S. Provisional PatentApplicationNo. 61/495,996, filed Jun. 11, 2011, and is a continuation-in-part of prior U.S. patent application Ser. No. 13/180,320, filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994, filed Jun. 11,2011, U.S. Provisional PatentApplicationNo. 61/495,997, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996, filed Jun. 11, 2011, and is a continuation-in-part 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page41 of 64 US 8,446,275 B2 3 4 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. non-provisional patent application Ser. No. 13/433,204 is also a continuationin-part of U.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011, which claims the benefit of U.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filed Jun. 11,2011 and is a continuation-in-part of U.S. patent application Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit of U.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part of U.S. patent application Ser. No. 13/158,416 filed Jun. 11,2011, which is a continuation-in-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,511 filed Jul. 12,2011 is also a continuationin-part of U.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit of U.S. Provisional PatentApplicationNo. 61/495,995 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filedJun. 11,2011 and is a continuation-in-part of U.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part of U.S. patent applica­ tion Ser. No. 13/158,372 filed Jun. 10, 2011; THIS applica­ tion is a continuation-in-part of U.S. non-provisional patent application Ser. No. 13/433,208, filed Mar. 28,2012, whichis a continuation-in-part of U.S. non-provisional patent appli­ cation Ser. No. of 13/181,495, filed Jul. 12, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/180,000, filed Jul. 11, 2011, which claims the benefit of U.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,996, filedJun. 11,2011, and U.S. patent application Ser. No. 13/180,000 is a continuation-in-part of prior U.S. patent application Ser. No. 13/158, 416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, and U.S. patent application Ser. No. 13/181,495 claims the benefit ofU.S. Provisional PatentApplicationNo. 61/495,995, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,997, filedJun. 11,2011, and U.S. Provisional PatentApplicationNo. 61/495,996, filed Jun. 11, 2011; U.S. patent application Ser. No. 13/181,495 is also a continuation-in-part of prior U.S. patent application Ser. No. 13/180,320, filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495, 995, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994, filed Jun. 11, 2011, U.S. Provisional Patent ApplicationNo. 61/495,997, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,996, filedJun. 11,2011, and U.S. patent application Ser. No. 13/180,320 is a continu­ ation-in-part of prior U.S. patent application Ser. No. 13/158, 416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provi­ sional Patent Application No. 61/495,994, filed Jun. 11,2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996, filed Jun. 11, 2011; U.S. patent application Ser. No. 13/181,495 is also a continuation-in-part of prior U.S. patent application Ser. No. 13/158,416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent applica­ tion Ser. No. 13/158,372, filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,495 is also a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011; U.S. non-provisional patent application Ser. No. 13/433,208 claims the benefit of U.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. ProvisionalPatentApplicationNo. 61/495,994, filed Jun. 11,2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, and U.S. Provisional PatentApplicationNo. 61/495,996, filed Jun. 11, 2011, and is a continuation-in-part of prior U.S. patent application Ser. No. 13/180,320, filed Jul. 11, 2011, which claims the benefit of U.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994, filedJun. 11,2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996, filed Jun. 11, 2011, and is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filedJun. 10, 2011, and also is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,416, filed Jun. 11, 2011, which is a continuationin-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, and is also a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011; U.S. non-provisional patent application Ser. No. 13/433,208 is also a continuation-in-part of U.S. Nonprovisional patent application Ser. No. 13/361,919, filed Jan. 30, 2012, which is a continuation ofU.S. Nonprovisional patent application Ser. No. 13/181,495 filed Jul. 12, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,996 filedJun. 11, 2011 and, U.S. Nonprovisional patent application Ser. No. 13/361,919 is a continuation-in-part ofU.S. patent application Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional PatentApplicationNo. 61/495, 995 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,996 filedJun. 11, 2011 and U.S. Nonprovisional patent application Ser. No. 13/361, 919 is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuationin-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. Nonprovisional patent application Ser. No. 13/181,495 filed Jul. 12, 2011 is also a continuation-inpart ofU.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. Nonprovisional 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page42 of 64 US 8,446,275 B2 5 6 patent application Ser. No. 13/361,919 is also a continuation of U.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011, which claims the benefit of U.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provi­ sional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part of U.S. patent application Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit of U.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filedJun. 11,2011 and is a continuation-in-part of U.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011 is also a continuation-inpart of U.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filedJun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. non-provisional patent application 13/433,208 is also a continuation-in-part ofU.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filedJun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filedJun. 11,2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011 is also a continuation-inpart ofU.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filedJun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; THIS application is a continuation-in-part ofU.S. non-provisional patent applica­ tion Ser. No. 13/433,213, filed Mar. 28, 2012, which is a continuation-in-part ofU.S. non-provisional patent application Ser. No. of 13/181,495, filed Jul. 12, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/180,000, filed Jul. 11, 2011, which claims the benefit of U.S. Provisional PatentApplicationNo. 61/495,995, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, U.S. Provi­ sional Patent Application No. 61/495,996, filed Jun. 11,2011, and U.S. patent application Ser. No. 13/180,000 is a continu­ ation-in-part of prior U.S. patent application Ser. No. 13/158, 416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, and U.S. patent application Ser. No. 13/181,495 claims the benefit of U.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994, filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997, filedJun. 11,2011, and U.S. Provisional PatentApplicationNo. 61/495,996, filed Jun. 11, 2011; U.S. patent application Ser. No. 13/181,495 is also a continuation-in-part of prior U.S. patent application Ser. No. 13/180,320, filed Jul. 11, 2011, which claims the benefit of U.S. Provisional Patent Application No. 61/495, 995, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994, filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,996, filedJun. 11,2011, and U.S. patent application Ser. No. 13/180,320 is a continu­ ation-in-part of prior U.S. patent application Ser. No. 13/158, 416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994, filedJun. 11,2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996, filed Jun. 11, 2011; U.S. patent application Ser. No. 13/181,495 is also a continuation-in-part of prior U.S. patent application Ser. No. 13/158,416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent applica­ tion Ser. No. 13/158,372, filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,495 is also a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011; U.S. non-provisional patent application Ser. No. 13/433,213 claims the benefit of U.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994, filed Jun. 11,2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, and U.S. Provisional PatentApplicationNo. 61/495,996, filed Jun. 11, 2011, and is a continuation-in-part of prior U.S. patent application Ser. No. 13/180,320, filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995, filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994, filedJun. 11,2011, U.S. Provisional Patent Application No. 61/495,997, filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996, filed Jun. 11, 2011, and is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,416, filed Jun. 11, 2011, which is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filedJun. 10, 2011, and also is a continuation-in-part of prior U.S. patent application Ser. No. 13/158,416, filed Jun. 11, 2011, which is a continuationin-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011, and is also a continuation-in-part of prior U.S. patent application Ser. No. 13/158,372, filed Jun. 10, 2011; U.S. non-provisional patent application Ser. No. 13/433,213 is also a continuation-in-part ofU.S. Nonprovisional patent application Ser. No. 13/361,919, filed Jan. 30, 2012, which is a continuation ofU.S. Nonprovisional patent application Ser. No. 13/181,495 filed Jul. 12, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page43 of 64 US 8,446,275 B2 7 8 U.S. Provisional PatentApplicationNo. 61/495,996 filed Jun. 11, 2011 and, U.S. Nonprovisional patent application Ser. No. 13/361,919 is a continuation-in-part of U.S. patent appli­ cation Ser. No. 13/180,000 filed Jul. 11, 2011, which claims thebenefitofU.S. Provisional PatentApplicationNo. 61/495, 995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,996 filed Jun. 11, 2011 and U.S. Nonprovisional patent application Ser. No. 13/361, 919 is a continuation-in-part of U.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuationin-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. Nonprovisional patent application Ser. No. 13/181,495 filed Jul. 12, 2011 is also a continuation-inpart of U.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. Nonprovisional patent application Ser. No. 13/361,919 is also a continuation ofU.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filedJun. 11,2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011 is also a continuation-inpart ofU.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filedJun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. non-provisional patent application Ser. No. 13/433,213 is also a continuationin-part ofU.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011, which claims the benefit ofU.S. Provisional PatentApplicationNo. 61/495,995 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filedJun. 11,2011 and is a continuation-in-part of U.S. patent application Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part of U.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,511 filed Jul. 12,2011 is also a continuationin-part of U.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit of U.S. Provisional PatentApplicationNo. 61/495,995 filed Jun. 11,2011,U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filed Jun. 11,2011 and is a continuation-in-part of U.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; THIS application claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,996 filed Jun. 11, 2011 and is also a continuation-in-part ofU.S. Nonpro­ visional patent application Ser. No. 13/361,919, filed Jan. 30, 2012, which is a continuation ofU.S. Nonprovisional patent application Ser. No. 13/181,495 filed Jul. 12, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,996 filed Jun. 11, 2011 and, is a continuation-in-part ofU.S. patent appli­ cation Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional PatentApplicationNo. 61/495, 995 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,996 filedJun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuationin-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. Nonprovisional patent application Ser. No. 13/181,495 filed Jul. 12, 2011 is also a continuation-inpart ofU.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. Nonprovisional patent application Ser. No. 13/361,919 is also a continuation ofU.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provi­ sional PatentApplicationNo. 61/495,994 filedJun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filedJun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/180,000 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Applica­ tion No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,994 filedJun. 11,2011,U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filed Jun. 11,2011 and is a continuation-in-part ofU.S. patent 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page44 of 64 US 8,446,275 B2 9 application Ser. No. 13/158,416 filed Jim. 11, 2011, which is a continuation-in-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011 is also a continuation-inpart of U.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provi­ sional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuation-in-part ofU.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; THIS application is also a continuation-in-part of U.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011, which claims the benefit of U.S. Provisional PatentApplicationNo. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495, 994 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filed Jun. 11,2011 and is a con­ tinuation-in-part ofU.S. patent application Ser. No. 13/180, 000 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional Patent Application No. 61/495,995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,99 4 filed Jun. 11, 2011, U.S. Provisional PatentApplicationNo. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158, 416 filed Jun. 11, 2011, which is a continuation-in-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011; U.S. patent application Ser. No. 13/181,511 filed Jul. 12, 2011 is also a continuation-in-part ofU.S. patent application Ser. No. 13/180,320 filed Jul. 11, 2011, which claims the benefit ofU.S. Provisional PatentApplicationNo. 61/495, 995 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,994 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,997 filed Jun. 11, 2011, U.S. Provisional Patent Application No. 61/495,996 filed Jun. 11, 2011 and is a continuation-in-part ofU.S. patent application Ser. No. 13/158,416 filed Jun. 11, 2011, which is a continuationin-part of U.S. patent application Ser. No. 13/158,372 filed Jun. 10, 2011, ALL of which are herein incorporated by reference for all purposes. 10 ing that users invest in multiple devices in order to perform different activities (e.g., a sports watch for tracking time and distance, a GPS receiver for monitoring a hike or run, a cyclometer for gathering cycling data, and others). Although 5 a wide range of data and information is available, conven­ tional devices and applications fail to provide effective solu­ tions that comprehensively capture data for a given user across numerous disparate activities. Some conventional solutions combine a small number of 10 discrete functions. Functionality for data capture, processing, storage, or communication in conventional devices such as a watch or timer with a heart rate monitor or global positioning system ("GPS") receiver are available conventionally, but are expensive to manufacture and purchase. Other conventional 15 solutions for combining personal data capture facilities often present numerous design and manufacturing problems such as size restrictions, specialized materials requirements, low­ ered tolerances for defects such as pits or holes in coverings 20 for water-resistant or waterproof devices, unreliability, higher failure rates, increased manufacturing time, and expense. Subsequently, conventional devices such as fitness watches, heart rate monitors, GPS-enabled fitness monitors, health monitors (e.g., diabetic blood sugar testing units), digital 25 voice recorders, pedometers, altimeters, and other conventional personal data capture devices are generally manufactured for conditions that occur in a single or small groupings of activities. Problematically, though, conventional devices do not provide effective solutions to users in terms of provid30 ing a comprehensive view of one's overall health or wellness as a result of a combined analysis of data gathered. This is a limiting aspect of the commercial attraction of the various types of conventional devices listed above. Generally, if the number of activities performed by con35 ventional personal data capture devices increases, there is a corresponding rise in design and manufacturing requirements that results in significant consumer expense, which eventually becomes prohibitive to both investment and commercialization. Further, conventional manufacturing techniques are 40 often limited and ineffective at meeting increased requirements to protect sensitive hardware, circuitry, and other components that are susceptible to damage, but which are required to perform various personal data capture activities. As a conventional example, sensitive electronic components 45 such as printed circuit board assemblies ("PCBA"), sensors, and computer memory (hereafter "memory") can be signifi­ FIELD cantly damaged or destroyed during manufacturing processes The present invention relates generally to electrical and where overmoldings or layering of protective material occurs electronic hardware, computer software, wired and wireless using techniques such as injection molding, cold molding, network communications, and computing devices. More spe- 50 and others. Damaged or destroyed items subsequently raises cifically, general health and wellness management techniques the cost of goods sold and can deter not only investment and and devices for use with a data-capable personal worn or commercialization, but also innovation in data capture and carried device are described. analysis technologies, which are highly compelling fields of opportunity. BACKGROUND 55 Thus, what is needed is a solution for data capture devices without the limitations of conventional techniques. With the advent of greater computing capabilities in smaller personal and/or portable form factors and an increas­ BRIEF DESCRIPTION OF THE DRAWINGS ing number of applications (i.e., computer and Internet soft­ ware or programs) for different uses, consumers (i.e., users) 60 Various embodiments or examples ("examples") of the have access to laige amounts of personal data. Information invention are disclosed in the following detailed description and the accompanying drawings: and data are often readily available, but poorly captured using conventional data capture devices. Conventional devices FIG. 1 illustrates an exemplary data-capable band system; typically lack capabilities that can capture, analyze, commu­ FIG. 2 illustrates a block diagram of an exemplary datanicate, or use data in a contextually-meaningful, comprehen- 65 capable band; sive, and efficient manner. Further, conventional solutions are FIG. 3 illustrates sensors for use with an exemplary dataoften limited to specific individual purposes or uses, demandcapable band; Case3:15-cv-02579 Document1-1 Filed06/10/15 Page45 of 64 US 8,446,275 B2 11 12 FIG. 4 illustrates an application architecture for an exem­ plary data-capable band; FIG. 5A illustrates representative data types for use with an exemplary data-capable band; FIG. 5B illustrates representative data types for use with an exemplary data-capable band in fitness-related activities; FIG. 5C illustrates representative data types for use with an exemplary data-capable band in sleep management activities; FIG. 5D illustrates representative data types for use with an exemplary data-capable band in medical-related activities; FIG. 5E illustrates representative data types for use with an exemplary data-capable band in social media/networkingrelated activities; FIG. 6 illustrates an exemplary communications device system implemented with multiple exemplary data-capable bands; FIG. 7 illustrates an exemplary wellness tracking system for use with or within a distributed wellness application; FIG. 8 illustrates representative calculations executed by an exemplary conversion module to determine an aggregate value for producing a graphical representation of a user's wellness; FIG. 9 illustrates an exemplary process for generating and displaying a graphical representation of a user's wellness based upon the user's activities; FIG. 10 illustrates an exemplary graphical representation of a user's wellness over a time period; FIG. 11 illustrates another exemplary graphical represen­ tation of a user's wellness over a time period; FIGS. 12A-12F illustrate exemplary wireframes of exem­ plary webpages associated with a wellness marketplace portal; FIG. 13 illustrates an exemplary computer system suitable for implementation of a wellness application and use with a data-capable band; FIG. 14 depicts an example of an aggregation engine, according to some examples; FIG. 15A depicts an example of an aggregation engine including a general health and wellness manager configured to operate with and/or control one or more managers, accord­ ing to some examples; FIG. 15B depicts an example of a flow to modify a target score to enhance a general health and wellness of a user, according to some examples; FIG. 16A depicts examples of a social manager and an environmental manager configured to generate a context score, according to some examples; FIG. 16B is an example of a flow diagram to determine recommendations based on a context score to manage health and wellness, according to some examples; FIGS. 16C and 16D depict examples of displays including feedback based on environmental or social parameters, according to some examples; FIG. 17A depicts an example of a general health and well­ ness manager, according to some examples; FIG. 17B is an example flow diagram for a technique of managing overall health and wellness using, for example, wearable devices that include sensors, according to some examples; and FIGS. 18A to 18D depict interrelationships between dif­ ferent aspects of health and wellness and different managers cooperating to optimize the same, according to various examples. tus, a user interface, or a series of program instructions on a computer readable medium such as a computer readable stor­ age medium or a computer network where the program instructions are sent over optical, electronic, or wireless com­ munication links. In general, operations of disclosed pro­ cesses may be performed in an arbitrary order, unless other­ wise provided in the claims. A detailed description of one or more examples is provided below along with accompanying figures. The detailed description is provided in connectionwith such examples, but is not limited to any particular example. The scope is limited only by the claims and numerous alternatives, modifications, and equivalents are encompassed. Numerous specific details are set forth in the following description in order to provide a thorough understanding. These details are provided for the purpose of example and the described techniques may be practiced according to the claims without some or all of these specific details. For clarity, technical material that is known in the technical fields related to the examples has not been described in detail to avoid unnecessarily obscuring the description. FIG. 1 illustrates an exemplary data-capable band system. Here, system 100 includes network 102, bands 104-112, server 114, mobile computing device 116, mobile communications device118, computer120, laptop 122, and distributed sensor 124. Bands 104-112 may be implemented as datacapable device that may be worn as a strap or band around an arm, leg, ankle, or other bodily appendage or feature. In other examples, bands 104-112 may be attached directly or indi­ rectly to other items, organic or inorganic, animate, or static. In still other examples, bands 104-112 may be used differ­ ently. As described above, bands 104-112 may be implemented as wearable personal data or data capture devices (e.g., datacapable devices) that are worn by a user around a wrist, ankle, arm, ear, or other appendage, or attached to the body or affixed to clothing. One or more facilities, sensing elements, or sensors, both active and passive, may be implemented as part of bands 104-112 in orderto capture various types of data from different sources. Temperature, environmental, tempo­ ral, motion, electronic, electrical, chemical, or other types of sensors (including those described below in connection with FIG. 3) may be used in order to gather varying amounts of data, which may be configurable by a user, locally (e.g., using user interface facilities such as buttons, switches, motionactivated/detected command structures (e.g., accelerometergathered data from user-initiated motion of bands 104-112), and others) or remotely (e.g., entering rules or parameters in a website or graphical user interface ("GUI") that may be used to modify control systems or signals in firmware, cir­ cuitry, hardware, and software implemented (i.e., installed) on bands104-112). Bands 104-112 may also be implemented as data-capable devices that are configured for data communication using various types of communications infrastructure and media, as described in greater detail below. Bands 104-112 may also be wearable, personal, non-intrusive, light­ weight devices that are configured to gather large amounts of personally relevant data that can be used to improve user health, fitness levels, medical conditions, athletic performance, sleeping physiology, and physiological conditions, or used as a sensory-based user interface ("UI") to signal socialrelated notifications specifying the state of the user through vibration, heat, lights or other sensory based notifications. For example, a social-related notification signal indicating a user is on-line can be transmitted to a recipient, who in turn, receives the notification as, for instance, a vibration. 5 10 15 20 25 30 35 40 45 50 55 60 DETAILED DESCRIPTION 65 Various embodiments or examples may be implemented in numerous ways, including as a system, a process, an appara- Case3:15-cv-02579 Document1-1 Filed06/10/15 Page46 of 64 US 8,446,275 B2 13 Using data gathered by bands 104-112, applications may be used to perform various analyses and evaluations that can generate information as to a person's physical (e.g., healthy, sick, weakened, or other states, or activity level), emotional, or mental state (e.g., an elevated body temperature or heart rate may indicate stress, a lowered heart rate and skin tem­ perature, or reduced movement (e.g., excessive sleeping), may indicate physiological depression caused by exertion or other factors, chemical data gathered from evaluating outgassing from the skin's surface may be analyzed to determine whether a person's diet is balanced or if various nutrients are lacking, salinity detectors may be evaluated to determine if high, lower, or proper blood sugar levels are present for dia­ betes management, and others). Generally, bands 104-112 may be configured to gather from sensors locally and remotely. As an example, band 104 may capture (i.e., record, store, communicate (i.e., send or receive), process, or the like) data from various sources (i.e., sensors that are organic (i.e., installed, integrated, or otherwise implemented with band 104) or distributed (e.g., microphones on mobile computing device 116, mobile communications device 118, computer 120, laptop 122, distributed sensor 124, global positioning system ("GPS") satellites, or others, without limitation)) and exchange data with one or more of bands106-112, server114, mobile computing device 116, mobile communications device 118, computer 120, laptop 122, and distributed sensor 124. As shown here, a local sensor may be one that is incor­ porated, integrated, or otherwise implemented with bands 104-112. A remote or distributed sensor (e g., mobile computing device 116, mobile communications device 118, com­ puter 120, laptop 122, or, generally, distributed sensor 124) may be sensors that can be accessed, controlled, or otherwise used by bands 104-112. For example, band 112 may be con­ figured to control devices that are also controlled by a given user (e.g., mobile computing device 116, mobile communi­ cations device118, computer120, laptop 122, and distributed sensor 124). For example, a microphone in mobile commu­ nications device 118 may be used to detect, for example, ambient audio data that is used to help identify a person's location, or an ear clip (e.g., a headset as described below) affixed to an ear may be used to record pulse or blood oxygen saturation levels. Additionally, a sensor implemented with a screen on mobile computing device 116 may be used to read a user's temperature or obtain a biometric signature while a user is interacting with data. A further example may include using data that is observed on computer 120 or laptop 122 that provides information as to a user's online behavior and the type of content that she is viewing, which may be used by bands 104-112. Regardless of the type or location of sensor used, data may be transferred to bands 104-112 by using, for example, an analog audio jack, digital adapter (e.g., USB, mini-USB), or other, without limitation, plug, or other type of connector that may be used to physically couple bands 104­ 112 to another device or system for transferring data and, in some examples, to provide power to rechaige a battery (not shown). Alternatively, a wireless data communication inter­ face or facility (e.g., a wireless radio that is configured to communicate data from bands 104-112 using one or more data communication protocols (e.g., IEEE 802.1 la/b/g/n (WiFi), WiMax, ANT™, ZigBee®, Bluetooth®, Near Field Communications ("NFC"), and others)) may be used to receive or transfer data. Further, bands 104-112 may be con­ figured to analyze, evaluate, modify, or otherwise use data gathered, either directly or indirectly. In some examples, bands 104-112 may be configured to share data with each other or with an intermediary facility, 14 such as a database, website, web service, or the like, which may be implemented by server 114. In some embodiments, server 114 can be operated by a third party providing, for example, social media-related services. Bands 104-112 and 5 0ther related devices may exchange data with each other directly, or bands 104-112 may exchangedata via a third party server, such as a third party like Facebook®, to provide social-media related services. Examples of other third party servers include those implemented by social networking ser­ 10 vices, including, but not limited to, services such as Yahoo! IM™, GTalk™, MSN Messenger™, Twitter® and other pri­ vate or public social networks. The exchanged data may include personal physiological data and data derived from 15 sensory-based user interfaces ("UI"). Server 114, in some examples, may be implemented using one or more processorbased computing devices or networks, including computing clouds, storage area networks ("SAN"), or the like. As shown, bands 104-112 may be used as a personal data or area network 20 (e.g., "PDN" or "PAN") in which data relevant to a given user or band (e.g., one or more of bands 104-112) may be shared. As shown here, bands 104 and 112 may be configured to exchange data with each other over network 102 or indirectly using server 114. Users of bands 104 and 112 may direct a 25 web browser hosted on a computer (e.g., computer 120, laptop 122, or the like) in order to access, view, modify, or perform other operations with data captured by bands104 and 112. For example, two runners using bands 104 and 112 may be geographically remote (e.g., users are not geographically 30 ^ close 35 40 45 50 55 60 65 roximity locall such that bands being usedb each user are in direct data communication), but wish to share data regarding their race times (pre, post, or in-race), personal records (i.e., "PR"), taiget split times, results, performance characteristics (e.g., target heart rate, target V02 max, and others), and other information. If both runners (i.e., bands 104 and 112) are engaged in a race on the same day, data can be gathered for comparative analysis and other uses. Further, data can be shared in substantially real-time (taking into account any latencies incurred by data transfer rates, network topologies, or other data network factors) as well as uploaded after a given activity or event has been performed. In other words, data can be captured by the user as it is worn and configured to transfer data using, for example, a wireless network connection (e.g., a wireless network interface card, wireless local area network ("LAN") card, cell phone, or the like). Data may also be shared in a temporally asynchronous manner in which a wired data connection (e.g., an analog audio plug (and associated software or firmware) configured to transfer digitally encoded data to encoded audio data that may be transferred between bands 104-112 and a plug con­ figured to receive, encode/decode, and process data exchanged) may be used to transfer data from one or more bands 104-112 to various destinations (e.g., another of bands 104-112, server 114, mobile computing device 116, mobile communications device 118, computer 120, laptop 122, and distributed sensor 124). Bands 104-112 may be implemented with various types of wired and/or wireless communication facilities and are not intended to be limited to any specific technology. For example, data may be transferred from bands 104-112 using an analog audio plug (e.g., TRRS, TRS, or others). In other examples, wireless communication facilities using various types of data communication protocols (e.g., WiFi, Bluetooth®, ZigBee®, ANT™, and others) may be implemented as part of bands 104-112, which may include circuitry, firmware, hardware, radios, antennas, processors, microprocessors, memories, or other electrical, electronic, Case3:15-cv-02579 Document1-1 Filed06/10/15 Page47 of 64 US 8,446,275 B2 15 16 mechanical, or physical elements configured to enable data communication capabilities of various types and characteris­ tics. As data-capable devices, bands 104-112 may be config­ ured to collect data from a wide range of sources, including onboard (not shown) and distributed sensors (e.g., server 114, mobile computing device 116, mobile communications device 118, computer 120, laptop 122, and distributed sensor 124) or other bands. Some or all data captured may be per­ sonal, sensitive, or confidential and various techniques for providing secure storage and access may be implemented. For example, various types of security protocols and algo­ rithms may be used to encode data stored or accessed by bands 104-112. Examples of security protocols and algo­ rithms include authentication, encryption, encoding, private and public key infrastructure, passwords, checksums, hash codes and hash functions (e.g., SHA, SHA-1, MD-5, and the like), or others may be used to prevent undesired access to data captured by bands 104-112. In other examples, data security for bands 104-112 may be implemented differently. Bands 104-112 may be used as personal wearable, data capture devices that, when worn, are configured to identify a specific, individual user. By evaluating captured data such as motion data from an accelerometer, biometric data such as heart rate, skin galvanic response, and other biometric data, and using long-term analysis techniques (e.g., software pack­ ages or modules of any type, without limitation), a user may have a unique pattern of behavior or motion and/or biometric responses that can be used as a signature for identification. For example, bands 104-112 may gather data regarding an individual person's gait or other unique biometric, physi­ ological or behavioral characteristics. Using, for example, distributed sensor 124, a biometric signature (e.g., finger­ print, retinal or iris vascular pattern, or others) may be gath­ ered and transmitted to bands 104-112 that, when combined with other data, determines that a given user has been prop­ erly identified and, as such, authenticated. When bands 104­ 112 are worn, a user may be identified and authenticated to enable a variety of other functions such as accessing or modi­ fying data, enabling wired or wireless data transmission facilities (i.e., allowing the transfer of data from bands 104­ 112), modifying functionality or functions of bands 104-112, authenticating financial transactions using stored data and information (e.g., credit card, PIN, card security numbers, and the like), running applications that allow for various operations to be performed (e.g., controlling physical secu­ rity and access by transmitting a security code to a reader that, when authenticated, unlocks a door by turning off current to an electromagnetic lock, and others), and others. Different functions and operations beyond those described may be performed using bands 104-112, which can act as secure, personal, wearable, data-capable devices. The number, type, function, configuration, specifications, structure, or other fea­ tures of system 100 and the above-described elements may be varied and are not limited to the examples provided. FIG. 2 illustrates a block diagram of an exemplary datacapable band. Here, band 200 includes bus 202, processor 204, memory 206, notification facility 208, accelerometer 210, sensor 212, battery 214, and communications facility 216. In some examples, the quantify, type, function, structure, and configuration of band 200 and the elements (e.g., bus 202, processor 204, memory 206, notification facility 208, accel­ erometer 210, sensor 212, battery 214, and communications facility 216) shown may be varied and are not limited to the examples provided. As shown, processor 204 may be implemented as logic to provide control functions and signals to memory 206, notification facility 208, accelerometer 210, sensor 212, battery 214, and communications facility 216. Processor 204 may be implemented using any type of proces­ sor or microprocessor suitable for packaging within bands 104-112 (FIG. 1). Various types of microprocessors may be used to provide data processing capabilities for band 200 and are not limited to any specific type or capability. For example, a MSP430F5528-type microprocessor manufactured by Texas Instruments of Dallas, Tex. may be configured for data communication using audio tones and enabling the use of an audio plug-and-jack system (e.g., TRRS, TRS, or others) for transferring data captured by band 200. Further, different processors may be desired if otherfunctionality (e.g., the type and number of sensors (e.g., sensor 212)) are varied. Data processed by processor 204 may be stored using, for example, memory 206. In some examples, memory 206 may be implemented using various types of data storage technologies and stan­ dards, including, without limitation, read-only memory ("ROM"), random access memory ("RAM"), dynamic random access memory ("DRAM"), static random access memory ("SRAM"), static/dynamic random access memory ("SDRAM"), magnetic random access memory ("MRAM"), solid state, two and three-dimensional memories, Flash®, and others. Memory 206 may also be implemented using one or more partitions that are configured for multiple types of data storage technologies to allow for non-modifiable (i.e., by a user) software to be installed (e.g., firmware installed on ROM) while also providing for storage of captured data and applications using, for example, RAM. Once captured and/or stored in memory 206, data may be subjected to various operations performed by other elements of band 200. Notification facility 208, in some examples, may be imple­ mented to provide vibratory eneigy, audio or visual signals, communicated through band 200. As used herein, "facility" refers to any, some, or all of the features and structures that are used to implement a given set of functions. In some examples, the vibratory energy may be implemented using a motor or other mechanical structure. In some examples, the audio sig­ nal may be a tone or other audio cue, or it may be implemented using different sounds for different purposes. The audio signals may be emitted directly using notification facil­ ity 208, or indirectly by transmission via communications facility 216 to other audio-capable devices (e.g., headphones (not shown), a headset (as described below with regard to FIG. 12), mobile computing device 116, mobile communications device 118, computer 120, laptop 122, distributed sen­ sor 124, etc.). In some examples, the visual signal may be implemented using any available display technology, such as lights, light-emitting diodes (LEDs), interferometric modulator display (IMOD), electrophoretic ink (E Ink), oiganic light-emitting diode (OLED), or other display technologies. As an example, an application stored on memory 206 may be configured to monitor a clock signal from processor 204 in order to provide timekeeping functions to band 200. For example, if an alarm is set for a desired time, notification facility 208 may be used to provide a vibration or an audio tone, or a series of vibrations or audio tones, when the desired time occurs. As another example, notification facility 208 may be coupled to a framework (not shown) or other structure that is used to translate or communicate vibratory energy throughout the physical structure of band 200. In other examples, notification facility 208 may be implemented dif­ ferently. Power may be stored in battery 214, which may be implemented as a battery, battery module, power management module, or the like. Power may also be gathered from local power sources such as solar panels, thermo-electric genera- 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page48 of 64 US 8,446,275 B2 17 18 tors, and kinetic eneigy generators, among others that are alternatives power sources to external power for a battery. These additional sources can either power the system directly or can charge a battery, which, in turn, is used to power the system (e.g., of a band). In other words, battery 214 may include a rechargeable, expendable, replaceable, or other type of battery, but also circuitry, hardware, or software that may be used in connection with in lieu of processor 204 in order to provide power management, charge/recharging, sleep, or other functions. Further, battery 214 may be implemented using various types of battery technologies, including Lithium Ion ("LI"), Nickel Metal Hydride ("NiMH"), or oth­ ers, without limitation. Power drawn as electrical current may be distributed from battery via bus 202, the latter of which may be implemented as deposited or formed circuitry or using other forms of circuits or cabling, including flexible circuitry. Electrical current distributed from battery 204 and managed by processor 204 may be used by one or more of memory 206, notification facility 208, accelerometer 210, sensor 212, or communications facility 216. As shown, various sensors may be used as input sources for data captured by band 200. For example, accelerometer 210 may be used to gather data measured across one, two, or three axes of motion. In addition to accelerometer 210, other sensors (i.e., sensor 212) may be implemented to provide temperature, environmental, physical, chemical, electrical, or other types of sensed inputs. As presented here, sensor 212 may include one or multiple sensors and is not intended to be limiting as to the quantity or type of sensor implemented. Data captured by band 200 using accelerometer 210 and sensor 212 or data requestedfrom another source (i.e., outside of band 200) may also be exchanged, transferred, or other­ wise communicated using communications facility 216. For example, communications facility 216 may include a wireless radio, control circuit or logic, antenna, transceiver, receiver, transmitter, resistors, diodes, transistors, or other elements that are used to transmit and receive data from band 200. In some examples, communications facility 216 may be imple­ mented to provide a "wired" data communication capability such as an analog or digital attachment, plug, jack, or the like to allow for data to be transferred. In other examples, com­ munications facility 216 may be implemented to provide a wireless data communication capability to transmit digitally encoded data across one or more frequencies using various types of data communication protocols, without limitation. In still other examples, band 200 and the above-described ele­ ments may be varied in function, structure, configuration, or implementation and are not limited to those shown and described. FIG. 3 illustrates sensors for use with an exemplary datacapable band. Sensor 212 may be implemented using various types of sensors, some of which are shown. Like-numbered and named elements may describe the same or substantially similar element as those shown in other descriptions. Here, sensor 212 (FIG. 2) may be implemented as accelerometer 302, altimeter/barometer 304, light/infrared ("IR") sensor 306, pulse/heart rate ("HR") monitor 308, audio sensor (e.g., microphone, transducer, or others) 310, pedometer 312, velocimeter 314, GPS receiver 316, location-based service sensor (e.g., sensor for determining location within a cellular or micro-cellular network, which may or may not use GPS or other satelliteconstellations for fixing a position) 318, motion detection sensor 320, environmental sensor 322, chemical sensor 324, electrical sensor 326, or mechanical sensor 328. As shown, accelerometer 302 may be used to capture data associated with motion detection along 1, 2, or 3-axes of measurement, without limitation to any specific type of speci- fication of sensor. Accelerometer 302 may also be imple­ mented to measure various types of user motion and may be configured based on the type of sensor, firmware, software, hardware, or circuitry used. As another example, altimeter/ barometer 304 may be used to measure environment pressure, atmospheric or otherwise, and is not limited to any specifica­ tion or type of pressure-reading device. In some examples, altimeter/barometer 304 may be an altimeter, a barometer, or a combination thereof. For example, altimeter/barometer 304 may be implemented as an altimeter for measuring above ground level ("AGL") pressure in band 200, which has been configured for use by naval or military aviators. As another example, altimeter/barometer 304 may be implemented as a barometer for reading atmospheric pressure for marine-based applications. In other examples, altimeter/barometer 304 may be implemented differently. Other types of sensors that may be used to measure light or photonic conditions include light/IR sensor 306, motion detection sensor 320, and environmental sensor 322, the latter of which may include any type of sensor for capturing data associated with environmental conditions beyond light. Fur­ ther, motion detection sensor 320 may be configured to detect motion using a variety of techniques and technologies, including, but not limited to comparative or differential light analysis (e.g., comparing foreground and background lighting), sound monitoring, or others. Audio sensor 310 may be implemented using any type of device configured to record or capture sound. In some examples, pedometer 312 may be implemented using devices to measure various types of data associated with pedestrian-oriented activities such as running or walk­ ing. Footstrikes, stride length, stride length or interval, time, and other data may be measured. Velocimeter 314 may be implemented, in some examples, to measure velocity (e.g., speed and directional vectors) without limitation to any particular activity. Further, additional sensors that may be used as sensor 212 include those configured to identify or obtain location-based data. For example, GPS receiver 316 may be used to obtain coordinates of the geographic location of band 200 using, for example, various types of signals transmitted by civilian and/or military satellite constellations in low, medium, or high earth orbit (e.g., "LEO," "MEO," or "GEO"). In other examples, differential GPS algorithms may also be implemented with GPS receiver 316, which may be used to generate more precise or accurate coordinates. Still further, location-based services sensor 318 may be imple­ mented to obtain location-based data including, but not lim­ ited to location, nearby services or items of interest, and the like. As an example, location-based services sensor 318 may be configured to detect an electronic signal, encoded or otherwise, that provides information regarding a physical locale as band 200 passes. The electronic signal may include, in some examples, encoded data regarding the location and information associated therewith. Electrical sensor 326 and mechanical sensor 328 may be configured to include other types (e.g., haptic, kinetic, piezoelectric, piezomechanical, pressure, touch, thermal, and others) of sensors for data input to band 200, without limitation. Other types of sensors apart from those shown may also be used, including magnetic flux sensors such as solid-state compasses and the like, including gyroscopic sensors. While the present illustration provides numerous examples of types of sensors that may be used with band 200 (FIG. 2), others not shown or described may be implemented with or as a substitute for any sensor shown or described, FIG. 4 illustrates an application architecture for an exem­ plary data-capable band. Here, application architecture 400 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page49 of 64 US 8,446,275 B2 19 20 includes bus 402, logic module 404, communications module 406, security module 408, interface module 410, data man­ agement 412, audio module 414, motor controller 416, ser­ vice management module 418, sensor input evaluation mod­ ule 420, and power management module 422. In some examples, application architecture 400 and the above-listed elements (e.g., bus 402, logic module 404, communications module 406, security module 408, interface module 410, data management 412, audio module 414, motor controller 416, service management module 418, sensor input evaluation module 420, and power management module 422) may be implemented as software using various computer program­ ming and formatting languages such as Java, C++, C, and others. As shown here, logic module 404 may be firmware or application software that is installed in memory 206 (FIG. 2) and executed by processor 204 (FIG. 2). Included with logic module 404 may be program instructions or code (e.g., source, object, binary executables, or others) that, when ini­ tiated, called, or instantiated, perform various functions. For example, logic module 404 may be configured to send control signals to communications module 406 in order to transfer, transmit, or receive data stored in memory 206, the latter of which may be managed by a database management system ("DBMS") or utility in data management module 412. As another example, security module 408 may be controlled by logic module 404 to provide encoding, decoding, encryp­ tion, authentication, or other functions to band 200 (FIG. 2). Alternatively, security module 408 may also be implemented as an application that, using data captured from various sen­ sors and stored in memory 206 (and accessed by data management module 412) may be used to provide identification functions that enable band 200 to passively identify a user or wearer of band 200. Still further, various types of security software and applications may be used and are not limited to those shown and described. Interface module 410, in some examples, may be used to manage user interface controls such as switches, buttons, or other types of controls that enable a user to manage various functions of band 200. For example, a 4-position switch may be turned to a given position that is interpreted by interface module 410 to determine the proper signal or feedback to send to logic module 404 in order to generate a particular result. In other examples, a button (not shown) may be depressed that allows a user to trigger or initiate certain actions by sending another signal to logic module 404. Still further, interface module 410 may be used to interpret data from, for example, accelerometer 210 (FIG. 2) to identify specific movement or motion that initiates or triggers a given response. In other examples, interface module 410 may be used to manage different types of displays (e.g., LED, IMOD, E Ink, OLED, etc.). In other examples, interface module 410 may be implemented differently in function, structure, or configuration and is not limited to those shown and described. As shown, audio module 414 may be configuredto manage encoded or unencoded data gathered from various types of audio sensors. In some examples, audio module 414 may include one or more codecs that are used to encode or decode various types of audio waveforms. For example, analog audio input may be encoded by audio module 414 and, once encoded, sent as a signal or collection of data packets, messages, segments, frames, or the like to logic module 404 for transmission via communications module 406. In other examples, audio module 414 may be implemented differently in function, structure, configuration, or implementation and is not limited to those shown and described. Other elements that may be used by band 200 include motorcontroller416, which may be firmware or an application to control a motor or other vibratory energy source (e.g., notification facility 208 (FIG. 2)). Power used for band 200 may be drawn from battery 214 (FIG. 2) and managed by power management module 422, which may be firmware or an application used to manage, with or without user input, how power is consumer, conserved, or otherwise used by band 200 and the above-de­ scribed elements, including one or more sensors (e.g., sensor 212 (FIG. 2), sensors 302-328 (FIG. 3)). With regard to data captured, sensor input evaluation module 420 may be a software engine or module that is used to evaluate and analyze data received from one or more inputs (e.g., sensors 302-328) to band 200. When received, data may be analyzed by sensor input evaluation module 420, which may include custom or "off-the-shelf analytics packages that are configured to provide application-specific analysis of data to determine trends, patterns, and other useful information. In other examples, sensor input module 420 may also include firmware or soft­ ware that enables the generation of various types and formats of reports for presenting data and any analysis performed thereupon, Another element of application architecture 400 that may be included is service management module 418. In some examples, service management module 418 may be firm­ ware, software, or an application that is configured to manage various aspects and operations associated with executing software-related instructions for band 200. For example, libraries or classes that are used by software or applications on band 200 may be served from an online or networked source. Service management module 418 may be implemented to manage how and when these services are invoked in order to ensure that desired applications are executed prop­ erly within application architecture 400. As discrete sets, collections, or groupings of functions, services used by band 200 for various purposes ranging from communications to operating systems to call or document libraries may be man­ aged by service management module 418. Alternatively, ser­ vice management module 418 may be implemented differ­ ently and is not limited to the examples provided herein. Further, application architecture 400 is an example of a software/system/application-level architecture that may be used to implement various software-related aspects of band 200 and may be varied in the quantity, type, configuration, func­ tion, structure, or type of programming or formatting lan­ guages used, without limitation to any given example. FIG. 5A illustrates representative data types for use with an exemplary data-capable band. Here, wearable device 502 may capture various types of data, including, but not limited to sensor data 504, manually-entered data 506, application data 508, location data 510, network data 512, system/operating data 514, and user data 516. Various types of data may be captured from sensors, such as those described above in connection with FIG. 3. Manually-entered data, in some examples, may be data or inputs received directly and locally by band 200 (FIG. 2). In other examples, manually-entered data may also be provided through a third-party website that stores the data in a database and may be synchronized from server 114 (FIG.1) with one ormore of bands 104-112. Other types of data that may be captured including application data 508 and system/operating data 514, which may be associated with firmware, software, or hardware installed or implemented on band 200. Further, location data 510 may be used by wearable device 502, as described above. User data 516, in some examples, may be data that include profile data, pref­ erences, rules, or other information that has been previously entered by a given user of wearable device 502. Further, network data 512 may be data is captured by wearable device with regard to routing tables, data paths, network or access 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page50 of 64 US 8,446,275 B2 21 22 availability (e.g., wireless network access availability), and the like. Other types of data may be captured by wearable device 502 and are not limited to the examples shown and described. Additional context-specific examples of types of data captured by bands 104-112 (FIG. 1) are provided below. FIG. 5B illustrates representative data types for use with an exemplary data-capable band in fitness-related activities. Here, band 519 may be configured to capture types (i.e., categories) of data such as heart rate/pulse monitoring data 520, blood oxygen saturation data 522, skin temperature data 524, salinity/emission/outgassing data 526, location/GPS data 528, environmental data 530, and accelerometer data 532. As an example, a runner may use or wear band 519 to obtain data associated with his physiological condition (i.e., heart rate/pulse monitoring data 520, skin temperature, salinity/emission/outgassing data 526, among others), athletic efficiency (i.e., blood oxygen saturation data 522), and per­ formance (i.e., location/GPS data 528 (e.g., distance or laps run), environmental data 530 (e.g., ambient temperature, humidity, pressure, and the like), accelerometer 532 (e.g., biomechanical information, including gait, stride, stride length, among others)). Other or different types of data may be captured by band 519, but the above-described examples are illustrative of some types of data that may be captured by band 519. Further, data captured may be uploaded to a website or online/networked destination for storage and other uses. For example, fitness-related data may be used by appli­ cations that are downloaded from a "fitness marketplace" or "wellness marketplace," where athletes, or other users, may find, purchase, or download applications, products, information, etc., for various uses, as well as share information with other users. Some applications may be activity-specific and thus may be used to modify or alter the data capture capabili­ ties of band 519 accordingly. For example, a fitness market­ place may be a website accessible by various types of mobile and non-mobile clients to locate applications for different exercise or fitness categories such as running, swimming, tennis, golf, baseball, football, fencing, and many others. When downloaded, applications from a fitness marketplace may also be used with user-specific accounts to manage the retrieved applications as well as usage with band 519, or to use thedata to provide services such as online personal coach­ ing or targeted advertisements. More, fewer, or different types of data may be captured for fitness-related activities. In some examples, applications may be developed using various types of schema, including using a software develop­ ment kit or providing requirements in a proprietary or open source software development regime. Applications may also be developed by using an application programming interface to an application marketplace in order for developers to design and build applications that can be downloaded on wearable devices (e.g., bands 104-106 (FIG. 1)). Alterna­ tively, application can be developed for download and instal­ lation on devices that may be in data communication over a shared data link or network connection, wired or wireless. For example, an application may be downloaded onto mobile computing device 116 (FIG. 1) from server 114 (FIG. 1), which may then be installed and executed using data gathered from one or more sensors on band 104. Analysis, evaluation, or other operations performed on data gathered by an application downloaded from server 114 may be presented (i.e., displayed) on a graphical user interface (e.g., a micro web browser, WAP web browser, Java/Java-script-based web browser, and others, without limitation) on mobile computing device 116 or any other type of client. Users may, in some examples, search, find, retrieve, download, purchase, or oth­ erwise obtain applications for various types of purposes from an application marketplace. Applications may be configured for various types of purposes and categories, without limita­ tion. Examples of types of purposes include running, swim­ ming, trail running, diabetic management, dietary, weight management, sleep management, caloric burn rate tracking, activity tracking, and others, without limitation. Examples of categories of applications may include fitness, wellness, health, medical, and others, without limitation. In other examples, applications for distribution via a marketplace or other download website or source may be implemented differently and is not limited to those described. FIG. 5C illustrates representative data types for use with an exemplary data-capable band in sleep management activities. Here, band 539 may be used for sleep management purposes to track various types of data, including heart rate monitoring data 540, motion sensor data 542, accelerometer data 544, skin resistivity data 546, user input data 548, clock data 550, and audio data 552. In some examples, heart rate monitor data 540 may be captured to evaluate rest, waking, or various states of sleep. Motion sensor data 542 and accelerometer data 544 may be used to determine whether a user of band 539 is experiencing a restful or fitful sleep. For example, some motion sensor data 542 may be captured by a light sensor that measures ambient or differential light patterns in order to determine whether a user is sleeping on her front, side, or back. Accelerometer data 544 may also be captured to deter­ mine whether a user is experiencing gentle or violent disrup­ tions when sleeping, such as those often found in afflictions of sleep apnea or other sleep disorders. Further, skin resistivity data 546 may be captured to determine whether a user is ill (e.g., running a temperature, sweating, experiencing chills, clammy skin, and others). Still further, user input data may include data input by a user as to how and whether band 539 should trigger notification facility 208 (FIG. 2) to wake a user at a given time or whether to use a series of increasing or decreasing vibrations or audio tones to trigger a waking state. Clock data (550) may be used to measure the durationof sleep or a finite period of time in which a user is at rest. Audio data may also be captured to determine whether a user is snoring and, if so, the frequencies and amplitude therein may suggest physical conditions that a user may be interested in knowing (e.g., snoring, breathing interruptions, talking in one's sleep, and the like). More, fewer, or different types of data may be captured for sleep management-related activities. FIG. 5D illustrates representative data types for use with an exemplary data-capable band in medical-related activities. Here, band 539 may also be configured for medical purposes and related-types of data such as heart rate monitoring data 560, respiratory monitoring data 562, body temperature data 564, blood sugar data 566, chemical protein/analysis data 568, patient medical records data 570, and healthcare profes­ sional (e.g., doctor, physician, registered nurse, physician's assistant, dentist, orthopedist, surgeon, and others) data 572. In some examples, data may be captured by band 539 directly from wear by a user. For example, band 539 may be able to sample and analyze sweat through a salinity or moisture detector to identify whether any particular chemicals, pro­ teins, hormones, or other oiganic or inorganic compounds are present, whichcan be analyzed by band 539 or communicated to server 114 to perform further analysis. If sent to server 114, further analyses may be performed by a hospital or other medical facility using data captured by band 539. In other examples, more, fewer, or different types of data may be captured for medical-related activities. FIG. 5E illustrates representative data types for use with an exemplary data-capable band in social media/networkingrelated activities. Examples of social media/networking-re- 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page51 of 64 US 8,446,275 B2 23 24 lated activities include activities related to Internet-based Social Networking Services ("SNS"), such as Facebook®, Twitter®, etc. Flere,band519, shownwithanaudio dataplug, may be configured to capture data for use with various types of social media and networking-related services, websites, and activities. Accelerometer data 580, manual data 582, other user/friends data 584, location data 586, network data 588, clock/timer data 590, and environmental data 592 are examples of data that may be gathered and shared by, for example, uploading data from band 519 using, for example, an audio plug such as those described herein. As another example, accelerometer data 580 may be captured and shared with other users to share motion, activity, or other movementoriented data. Manual data 582 may be data that a given user also wishes to share with other users. Likewise, other user/ friends data 584 may be from other bands (not shown) that can be shared or aggregated with data captured by band 519. Location data 586 for band 519 may also be shared with other users. In other examples, a user may also enter manual data 582 to prevent other users or friends from receiving updated location data from band 519. Additionally, network data 588 and clock/timer data may be captured and shared with other users to indicate, for example, activities or events that a given user (i.e., wearing band 519) was engaged at certain locations. Further, if a user of band 519 has friends who are not geographically located in close or near proximity (e.g., the user of band 519 is located in San Francisco and her friend is located in Rome), environmental data can be captured by band 519 (e.g., weather, temperature, humidity, sunny or overcast (as interpreted from data captured by alight sensor and combined with captured data for humidity and temperature), among others). In other examples, more, fewer, or different types of data may be captured for medical-related activities. FIG. 6 illustrates an exemplary communications device system implemented with multiple exemplary data-capable bands. The exemplary system 600 shows exemplary lines of communication between some of the devices shown in FIG. 1, including network 102, bands 104-110, mobile communications device 118, and laptop 122. In FIG. 6, examples of both peer-to-peer communication and peer-to-hub communication using bands 104-110 are shown. Using these avenues of communication, bands worn by multiple users or wearers (the term "wearer" is used herein to describe a user that is wearing one or more bands) may monitor and compare physi­ cal, emotional, mental states among wearers (e.g., physical competitions, sleep pattern comparisons, resting physical states, etc.). Peer-to-hub communication may be exemplified by bands 104 and 108, each respectively communicating with mobile communications device 118 or laptop 122, exemplary hub devices. Bands 104 and 108 may communicate with mobile communications device 118 or laptop 122 using any number of known wired communication technologies (e.g., Universal Service Bus (USB) connections, TRS/TRRS connections, telephone networks, fiber-optic networks, cable networks, etc.). In some examples, bands 104 and 108 may be implementedaslowerpowerorlowerenergydevices,inwhichcase mobile communications device 118, laptop 122 or other hub devices may act as a gateway to route the data from bands 104 and 108 to software applications on the hub device, or to other devices. For example, mobile communications device 118 may comprise both wired and wireless communication capabilities, and thereby act as a hub to further communicate data received from band 104 to band 110, network 102 or laptop 122, among other devices. Mobile communications device 118 also may comprise software applications that interact with social or professional networking services ("SNS") (e.g., Facebook®, Twitter®, Linkedln®, etc.), for example via network 102, and thereby act also as ahub to further share data received from band 104 with other users of the SNS. Band 104 may communicate with laptop 122, which also may comprise both wired and wireless communication capabilities, and thereby act as a hub to further communicate data received from band 104 to, for example, network 102 or laptop 122, among other devices. Laptop 122 also may comprise software applications that interact with SNS, for example via network 102, and thereby act also as a hub to further share data received from band 104 with other users of the SNS. The software applications on mobile communications device 118 or laptop 122 or other hub devices may further process or analyze the data they receive from bands 104 and 108 in order to present to the wearer, or to other wearers or users of the SNS, useful information associated with the wearer's activities: In other examples, bands 106 and 110 may also participate in peer-to-hub communications with exemplary hub devices such as mobile communications device 118 and laptop 122. Bands 106 and 110 may communicate with mobile communications device 118 and laptop 122 using any number of wireless communication technologies (e.g., local wireless network, near field communication, Bluetooth®, Bluetooth® low eneigy, ANT, etc.). Using wireless communication technologies, mobile communications device118 and laptop 122 may be used as a hub or gateway device to communicate data captured by bands 106 and 110 with other devices, in the same way as described above with respect to bands 104 and 108. Mobile communications device118 and laptop 122 also may be used as a hub or gateway device to further share data captured by bands 106 and 110 with SNS, in the same way as described above with respect to bands 104 and 108. Peer-to-peer communication may be exemplified by bands 106 and 110, exemplary peer devices, communicating directly. Band 106 may communicate directly with band 110, and vice versa, using known wireless communication technologies, as described above. Peer-to-peer communication may also be exemplified by communications between bands 104 and 108 and bands 106 and 110 through a hub device, such as mobile communications device 118 or laptop 122. Alternatively, exemplary system 600 may be implemented with any combination of communication capable devices, such as any of the devices depicted in FIG. 1, communicating with each other using any communication platform, including any of the platforms described above. Persons of ordinary skill in the art will appreciate that the examples of peer-to-hub communication provided herein, and shown in FIG. 6, are only a small subset of the possible implementations of peerto-hub communications involving the bands described herein, FIG. 7 illustrates an exemplary wellness tracking system for use with or within a distributed wellness application. System 700 comprises aggregation engine 710, conversion module 720, band 730, band 732, textual input 734, other input 736, and graphical representation 740. Bands 730 and 732 may be implemented as described above. In some examples, aggregation engine 710 may receive input from various sources. For example, aggregation engine 710 may receive sensory input from band 730, band 732, and/or other data-capable bands. This sensory input may include any of the above-described sensory data that may be gathered by data-capable bands. In other examples, aggregation engine 710 may receive other (e.g., manual) input from textual input 734 or other input 736. Textual input 734 and other input 736 may include information that a user types, uploads, or otherwise inputs into an application (e.g., a web application, an 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page52 of 64 US 8,446,275 B2 25 26 iPhone® application, etc.) implemented on any of the data and communications capable devices referenced herein (e.g., computer, laptop, computer, mobile communications device, mobile computing device, etc.). In some examples, aggrega­ tion engine 720 may be configured to process (e.g., interpret) the data and information received from band 730, band 732, textual input 734 and other input 736, to determine an aggre­ gate value from which graphical representation 740 may be generated. In an example, system 700 may comprise a con­ version module 720, which may be configured to perform calculations to convert the data received from band 730, band 732, textual input 734 and other input 736 into values (e.g., numeric values). Those values may then be aggregated by aggregation engine 710 to generate graphical representation 740. Conversion module 720 may be implemented as part of aggregation engine 710 (as shown), or it may be implemented separately (not shown). In some examples, aggregation engine 710 may be implemented with more or different mod­ ules. In other examples, aggregation engine 710 may be implemented with fewer or more input sources. In some examples, graphical representation 740 may be implemented differently, using different facial expressions, or any image or graphic according to any intuitive or predetermined set of graphics indicating various levels and/or aspects of wellness. As described in more detail below, graphical representation 740 may be a richer display comprising more than a single graphic or image (e.g., FIGS. 10 and 11). In some examples, aggregation engine 710 may receive or gather inputs from one or more sources over a period of time, or over multiple periods of time, and organize those inputs into a database (not shown) or other type of oiganized form of information storage. In some examples, graphical represen­ tation 740 may be a simple representation of a facial expres­ sion, as shown. In other examples, graphical representation 740 may be implemented as a richer graphical display comprising inputs gathered over time (e.g., FIGS. 10 and 11 below). FIG. 8 illustrates representative calculations executed by an exemplary conversion module to determine an aggregate value for producing a graphical representation of a user's wellness. In some examples, conversion module 820 may be configured to process data associated with exercise, data associated with sleep, data associated with eating or food intake, and data associated with other miscellaneous activity data (e.g., sending a message to a friend, gifting to a friend, donating, receiving gifts, etc.), and generate values from the data. For example, conversion module 820 may perform cal­ culations using data associated with activities ("activity data") to generate values for types of exercise (e.g., walking, vigorous exercise, not enough exercise, etc.) (810), types of sleep (e.g., deep sleep, no sleep, not enough deep sleep, etc.) (812), types of meals (e.g., a sluggish/heavy meal, a good meal, an energizing meal, etc.) (814), or other miscellaneous activities (e.g., sending a message to a friend, gifting to a friend, donating, receiving gifts, etc.) (816). Note that while in this example types of sleep 812, types of meals 814, and miscellaneous activities 816 are expressed in numbers of steps, FIG. 8 is not intended to be limiting is one of numerous ways in which to express types of sleep 812, types of meals 814, and miscellaneous activities 816. For example, types of sleep 812, types of meals 814, and miscellaneous activities 816 can correspond to different point values of which one or more scores can be derived to determine aggregate value 830, which can be expressed in terms of points or a score. In some implementations, these values may include positive values for activities that are beneficial to a user's wellness and nega­ tive values for activities that are detrimental to a user's well- ness, or for lack of activity (e.g., not enough sleep, too many minutes without exercise, etc.). In one example, the values may be calculated using a reference activity. For example, conversion module 820 may equate a step to the numerical value 0.0001, and then equate various other activities to a number of steps (810, 812, 814, 816). In some examples, these values may be weighted according to the quality of the activity. For example, each minute of deep sleep equals a higher number of steps than each minute of other sleep (812). As described in more detail below (FIGS. 10 and 11), these values may be modulated by time. For example, positive values for exercise may be modulated by negative values for extended time periods without exercise (810). In another example, positive values for sleep or deep sleep may be modulated by time without sleep or not enough time spent in deep sleep (812). In some examples, conversion module 820 is configured to aggregate these values to generate an aggre­ gate value 830. In some examples, aggregate value 830 may be used by an aggregation engine (e.g., aggregation engine 710 described above) to generate a graphical representation of a user's wellness (e.g., graphical representation 740 described above, FIGS.10 and 11 described below, or others). FIG. 9 illustrates an exemplary process for generating and displaying a graphical representation of a user's wellness based upon the user's activities. Process 900 may be implemented as an exemplary process for creating and presenting a graphical representation of a user's wellness. In some examples, process 900 may begin with receiving activity data from a source (902). For example, the source may comprise one of the data-capable bands described herein (e.g., band 730, band 732, etc.). In another example, the source may comprise another type of data and communications capable device, such as those described above (e.g., computer, laptop, computer, mobile communications device, mobile computing device, etc.), which may enable a user to provide activity data via various inputs (e.g., textual input 734, other input 736, etc.). For example, activity data may be received from a data-capable band. In another example, activity data may be received from data manually input using an application user interface via a mobile communications device or a laptop. In other examples, activity data may be received from sources or combinations of sources. After receiving the activity data, another activity data is received from another source (904). The another source also may be any of the types of sources described above. Once received, the activity data from the source, and the another activity data from another source, is then used to determine (e.g., by conversion module 720 or 730, etc.) an aggregate value (906). Once determined, the aggregate value is used to generate a graphical representation of a user's present wellness (908) (e.g., graphical representation 740 described above, etc.). The aggregate value also may be combined with other information, of the same type or different, to generate a richer graphical representation (e.g., FIGS. 10 and 11 described below, etc.). In other examples, activity data may be received from multiple sources. These multiple sources may comprise a combination of sources (e.g., a band and a mobile communi­ cations device, two bands and a laptop, etc.) (not shown). Such activity data may be accumulated continuously, periodically, or otherwise, over a time period. As activity data is accumulated, the aggregate value may be updated and/or accumulated, and in turn, the graphical representation may be updated. In some examples, as activity data is accumulated and the aggregate value updated and/or accumulated, additional graphical representations may be generated based on the updated or accumulated aggregate value(s). In other examples, the above-described process may be varied in the 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page53 of 64 US 8,446,275 B2 27 28 implementation, order, function, or structure of each or all steps and is not limited to those provided. FIG. 10 illustrates an exemplary graphical representation of a user's wellness over a time period. Here, exemplary graphical representation 1000 shows a user's wellness progress over the course of a partial day. Exemplary graphical representation 1000 may comprise a rich graph displaying multiple vectors of data associated with a user's wellness over time, including a status 1002, a time 1004, alarm graphic 1006, points progress line1008, points gained for completion of activities 1012-1016, total points accumulated 1010, graphical representations 1030-1034 of a user's wellness at specific times over the time period, activity summary data and analysis over time (1018-1022), and an indication of syncing activity 1024. Flere, status 1002 may comprise a brief (e.g., single word) general summary of a user's wellness. In some examples, time1004 may indicate the current time, or in other examples, it may indicate the time that graphical representa­ tion 1000 was generated or last updated. In some other examples, time 1004 may be implemented using different time zones. In still other examples, time 1004 may be imple­ mented differently. In some examples, alarm graphic 1006 may indicate the time that the user's alarm rang, or in other examples, it may indicate the time when a band sensed the user awoke, whether or not an alarm rang. In other examples, alarm graphic 1006 may indicate the time when a user's band began a sequence of notifications to wake up the user (e.g., using notification facility 208, as described above), and in still other examples, alarm graphic 1006 may represent something different. As shown here, graphical representation 1000 may include other graphical representations of the user's wellness at specific times of the day (1030,1032,1034), for example, indicating a low level of wellness or low energy level soon after waking up (1030) and a more alert or higher energy or wellness level after some activity (1032, 1034). Graphical representation 1000 may also include displays of various analyses of activity over time. For example, graphical repre­ sentation may include graphical representations of the user's sleep (1018), including how many total hours slept and the quality ofsleep(e.g., bars may represent depth of sleep during periods of time). In another example, graphical representa­ tion may include graphical representations of various aspects of a user's exercise level for a particular workout, including the magnitude of the activity level (1020), duration (1020), the number of steps taken (1022), the user's heart rate during the workout (not shown), and still other useful information (e.g., altitude climbed, laps of a pool, number of pitches, etc.). Graphical representation 1000 may further comprise an indi­ cation of syncing activity (1024) showing that graphical rep­ resentation 1000 is being updated to include additional information from a device (e.g., a data-capable band) or application. Graphical representation 1000 may also include indications of a user's total accumulated points 1010, as well as points awarded at certain times for certain activities (1012, 1014,1016). For example, shown here graphical representation 1000 displays the user has accumulated 2,017 points in total (e.g., over a lifetime, over a set period of time, etc.) mic load of the meal (e.g., a meal with low glycemic load may have positive effects that meal carry over to subsequent meals, whereas a meal with a higher glycemic load may have a positive effect only until the next meal). In some examples, auser'stotalaccumulatedpointslOlOmayreflectthatcertain points have expired and are no longer valid. In some examples, these points may be used for obtaining various types of rewards, or as virtual or actual currency, for example, in an online wellness marketplace, as described herein (e.g., a fitness marketplace). For example, points may be redeemed for virtual prizes (e.g., for games, challenges, etc.), or physical goods (e.g., products associated with a user's goals or activities, higher level bands, which may be distinguished by different colors, looks and/or features, etc.). In some examples, the points may automatically be tracked by a provider of data-capable bands, such that a prize (e.g., higher level band) is automatically sent to the user upon reaching a given points threshold without any affirmative action by the user. In other examples, a user may redeem a prize (e.g., higher level band) from a store. In still other examples, a user may receive deals. These deals or virtual prizes may be received digitally via a data-capable band, a mobile communications device, or otherwise. FIG. 11 illustrates another exemplary graphical representation of a user's wellness over a time period. Here, exemplary graphical representation 1100 shows a summary of a user's wellness progress over the course of a week. Exem­ plary graphical representation 1100 may comprise a rich graph displaying multiple vectors of data associated with a user's wellness overtime, including a status 1102, a time 1104, summary graphical representations 1106-1116 of a user's wellness on each days, points earned each day 1120­ 1130, total points accumulated 1132, points progress line 1134, an indication of syncing activity 1118, and bars 11361140. Here, as with status 1002 in FIG. 10, status 1102 may comprise a brief (e.g., single word) general summary of a user's wellness. In some examples, time 1104 may indicate the current time, or in other examples, it may indicate the time that graphical representation 1100 was generated or last updated. In some other examples, time 1104 may be implemented using different time zones. In still other examples, time 1104 may be implemented differently. As shown here, graphical representation 1100 may include summary graphi­ cal representations 1106-1116 of the user's wellness on each day, for example, indicating a distress or tiredness on Wednesday (1110) or a positive spike in wellness on Friday (1116). In some examples, summary graphical representa­ tions 1106-1116 may indicate a summary wellness for that particular day. In other examples, summary graphical representations 1106-1116 may indicate a cumulative wellness, e.g., at the end of each day. Graphical representation 1100 may further comprise an indication of syncing activity 1118 showing that graphical representation 1100 is being updated to include additional information from a device (e.g., a datacapable band) or application. Graphical representation 1100 may also include indications of a user's total accumulated points 1132, as well as points earned each day 1120-1130. For example, shown here graphical representation 1100 displays the user has accumulated 2,017 points thus far, which includes 325 points earned on Saturday (1130), 263 points earned on Friday (1128), 251 points earned on Thursday (1126), and so on. As described above, these points may be used for obtaining various types of rewards, or as virtual or actual currency, for example, in an online wellness marketplace (e.g., a fitness marketplace as described above). In some examples, graphical representation 1100 also may comprise bars 1136-1140. Each bar may represent an aspect of a user's 5 10 15 20 25 30 35 40 45 50 55 (1010). In some examples, points awarded may be time-dependent or may expire after a period of time. For example, points 60 awarded for eating a good meal may be valid only for a certain period of time. This period of time may be a predetermined period of time, or it may be dynamically determined. In an example where the period of time is dynamically determined, the points may be valid only until the user next feels hunger. 65 In another example where the period of time is dynamically determined, the points may be valid depending on the glyce- Case3:15-cv-02579 Document1-1 Filed06/10/15 Page54 of 64 US 8,446,275 B2 29 wellness (e.g., food, exercise, sleep, etc.). In some examples, the bar may display the user's daily progress toward a per­ sonal goal for each aspect (e.g., to sleep eight hours, complete sixty minutes of vigorous exercise, etc.). In other examples, the bar may display the user's daily progress toward a standardized goal (e.g., a health and fitness expert's published guidelines, a government agency's published guidelines, etc.), or other types of goals. FIGS. 12A-12F illustrate exemplary wireframes of exem­ plary webpages associated with a wellness marketplace. Here, wireframe 1200 comprises navigation 1202, selected page 1204A, sync widget 1216, avatar and goals element 1206, statistics element 1208, information ticker 1210, social feed 1212, check-in/calendar element 1214, deal element 1218, and team summary element 1220. As described above, a wellness marketplace may be implemented as a portal, website or application where users, may find, purchase, or download applications, products, information, etc., for vari­ ous uses, as well as share information with other users (e.g., users with like interests). Here, navigation 1202 comprises buttons and widgets for navigating through various pages of the wellness marketplace, including the selected page 1204A1204F (e.g., the Home page, Team page, Public page, Move page, Eat page, Live page, etc.) and sync widget 1216. In some examples, sync widget 1216 may be implemented to sync a data-capable band to the user's account on the wellness marketplace. In some examples, the Home page may include avatar and goals element 1206, which may be configured to display a user's avatar and goals. Avatar and goals element 1206 also may enable a user to create an avatar, either by selecting from predetermined avatars, by uploading a user's own picture or graphic, or other known methods for creating an avatar. Avatar and goals element 1206 also may enable a user to set goals associated with the user's health, eating/ drinking habits, exercise, sleep, socializing, or other aspects of the user's wellness. The Home page may further include statistics element 1208, which may be implemented to dis­ play statistics associated with the user's wellness (e.g., the graphical representations described above). As shown here, in some examples, statistics element 1208 may be implemented as a dynamic graphical, and even navigable, element (e.g., a video or interactive graphic), wherein a user may view the user's wellness progress over time. In other examples, the statistics element 1208 may be implemented as described above (e.g., FIGS. 10 and 11). The Home page may further include information ticker 1210, which may stream informa­ tion associated with a user's activities, or other information relevant to the wellness marketplace. The Home page may further include social feed 1212, which may be implemented as a scrolling list of messages or information (e.g., encouragement, news, feedback, recommendations, comments, etc.) from friends, advisors, coaches, or other users. The messages or information may include auto-generated encouragement, comments, news, recommendations, feedback, achieve­ ments, opinions, actions taken by teammates, or other information, by a wellness application in response to data associ­ ated with the user's wellness and activities (e.g., gathered by a data-capable band). In some examples, social feed 1212 may be searchable. In some examples, social feed 1212 may enable a user to filter or select the types of messages or information that shows up in the feed (e.g., from the public, only from the team, only from the user, etc.). Social feed1212 also may be configured to enable a user to select an action associated with each feed message (e.g., cheer, follow, gift, etc.).Insomeexamples,check-in/calendarelementl214may be configured to allow a user to log their fitness and nutrition. In some examples, check-in/calendar element 1214 also may 30 be configured to enable a user to maintain a calendar. Deal element 1218 may provide a daily deal to the user. The daily deal may be featured for the marketplace, it may be associated with the user's activities, or it may be generated using a 5 variety ofknownadvertisingmodels. Team summary element 1220 may provide summary information about the user's team. As used herein, the term "team" may refer to any group of users that elect to use the wellness marketplace together. In some examples, a user may be part of more than one team. In 10 other examples, a group of users may form different teams for different activities, or they may form a single team that par­ ticipates in, tracks, and shares information regarding, more than one activity. A Home page may be implemented differ­ ently than described here. 15 Wireframe 1230 comprises an exemplary Team page, which may include a navigation 1202, selected page 1204B, sync widget 1216, team manager element 1228, leaderboard element 1240, comparison element 1242, avatar and goals element 1206A, statistics element 1208A, social feed 1212A, 20 and scrolling member snapshots element 1226. Avatar and goals element 1206A and statistics element 1208A may be implemented as described above with regard to like-num­ bered or corresponding elements. Navigation 1202, selected page 1204B and sync widget 1216 also may be implemented 25 as described above with regard to like-numbered or correspending elements. In some examples, team manager ele­ ment 1228 may be implemented as an area for displaying information, or providing widgets, associatedwith team man­ agement. Access to team manager element 1228 may be 30 restricted, in some examples, or access may be provided to the entire team. Leaderboard element 1240 may be implemented to display leaders in various aspects of an activity inwhich the team is participating (e.g., various sports, social functions (e.g., clubs), drinking abstinence, etc.). In some examples, 35 leaderboard element 1240 may be implemented to display leaders among various groupings (e.g., site-wide, team only, other users determined to be "like" the user according to certain criteria (e.g., similar activities), etc.). In other examples, leaderboard element 1240 may be oiganized or 40 filtered by various parameters (e.g., date, demographics, geography, activity level, etc.). Comparison element 1242 may be implemented, in some examples, to provide compari­ sons regarding a user's performance with respect to an activ­ ity, or various aspects of an activity, with the performance of 45 the user's teammates or with the team as a whole (e.g., team average, team median, team favorites, etc.). Scrolling mem­ ber snapshots element 1226 may be configured to provide brief summary information regarding each of the members of the team in a scrolling fashion. A Team page may be imple50 mented differently than described here, Wireframe 1250 comprises an exemplary Public page, which may include navigation 1202, selected page 1204C, sync widget 1216, leaderboard element 1240A, social feed 1212B, statistics report engine 1254, comparison element 55 1242A, and challenge element 1256. Navigation 1202, selected page 1204C and sync widget 1216 may be imple­ mented as described above with regard to like-numbered or corresponding elements. Leaderboard element 1240A also may be implemented as described above with regard to lead60 erboard element 1240, and in some examples, may display leaders amongst all of the users of the wellness marketplace. Social feed 1212B also may be implemented as described above with regard social feed 1212 and social feed 1212A. Comparison element 1242A may be implemented as 65 described above with regard to comparison element 1242, and in some examples, may display comparisons of a user's performance of an activity against the performance of all of Case3:15-cv-02579 Document1-1 Filed06/10/15 Page55 of 64 US 8,446,275 B2 31 32 the other users of the wellness marketplace. Statistics report and/or supplement each day. An Eat page may be imple­ mented differently than described here. engine 1254 may generate and display statistical reports asso­ Wireframe 1280 comprises an exemplary Live page, which ciated with various activities being monitored by, and dismay include navigation 1202, selected page 1204F, sync widcussed in, the wellness marketplace. In some examples, chal­ lenge element 1256 may enable a user to participate in 5 get 1216, leaderboard element 1240E, search and recommen­ dations element 1272, product sales element 1282, maps ele­ marketplace-wide challenges with other users. In other ment 1280B, social feed 1212C, health research element examples, challenge element 1256 may display the status of, 1286, and product research element 1290. Navigation 1202, or other information associated with, ongoing challenges selected page 1204F, sync widget 1216, leaderboard element among users. A Public page may be implemented differently 10 1240E, search and recommendations element 1272, product than described here. sales element 1282, maps element 1280B and social feed Wireframe 1260 comprises an exemplary Move page, 1212C may be implemented as described above with regard which may include navigation 1202, selected page 1204D, to like-numbered or corresponding elements. In some sync widget 1216, leaderboard element 1240B, statistics examples, the Live page may include health research element report engine 1254, comparison element 1242B, search and 15 1286 configured to display, or to enable a user to research, recommendations element 1272, product sales element 1282, information regarding health topics. In some examples, the exercise science element 1264, daily movement element Live page may include product research element 1290 con­ 1266, maps element 1280 and titles element1258. Navigation figured to display, or to enable a user to research, information 1202, selected page 1204D, sync widget 1216, leaderboard regarding products. In some examples, the products may be element 1240B, statistics report engine1254, and comparison 20 associated with a user's particular activities or activity level, element 1242B may be implemented as described above with In otherexamples, the products may be associated with any of the activities monitored by, or discussed on, the wellness regard to like-numbered or corresponding elements. The marketplace. A Live page may be implemented differently Move page may be implemented to include a search and than described here. recommendations element 1272, which may be implemented to enable searching of the wellness marketplace. In some 25 FIG. 13 illustrates an exemplary computer system suitable examples, in addition to results of the search, recommenda­ for implementation of a wellness application and use with a tions associated with the user's search may be provided to the data-capable band. In some examples, computer system 1300 user. In other examples, recommendations may be provided may be used to implement computer programs, applications, to the user based on any other data associated with the user's methods, processes, or other software to perform the aboveactivities, as received by, gathered by, or otherwise input into, 30 described techniques. Computer system 1300 includes a bus the wellness marketplace. Product sales element1282 may be 1302 or other communicationmechanism forcommunicating implemented to display products for sale and provide widgets information, which interconnects subsystems and devices, to enable purchases of products by users. The products may such as processor 1304, system memory 1306 (e.g., RAM), be associated with the user's activities or activity level. Daily storage device 1308 (e.g., ROM), disk drive 1310 (e.g., magmovement element 1266 may be implemented to suggest an 35 netic or optical), communication interface 1312 (e.g., modem exercise each day. Maps element 1280 may be implemented or Ethernet card), display 1314 (e.g., CRT or LCD), input to display information associated with the activity of users of device 1316 (e.g., keyboard), and cursor control 1318 (e.g., the wellness marketplace on a map. In some examples, maps mouse or trackball). element 1280 may display a percentage of users that are According to some examples, computer system 1300 perphysically active in a geographical region. In other examples, 40 forms specific operations by processor1304 executing one or maps element 1280 may display a percentage of users that more sequences of one or more instructions stored in system have eaten well over a particular time period (e.g., currently, memory 1306. Such instructions may be read into system today, this week, etc.). In still other examples, maps element memory 1306 from another computer readable medium, such 1280 may be implemented differently. In some examples, as static storage device 1308 or disk drive 1310. In some titles element 1258 may display a list of users and the titles 45 examples, hard-wired circuitry may be used in place of or in they have earned based on their activities and activity levels combination with software instructions for implementation. The term "computer readable medium" refers to any tan­ (e.g., a most improved user, a hardest working user, etc.). A Move page may be implemented differently than described gible medium that participates in providing instructions to here. processor 1304 for execution. Such a medium may take many Wireframe 1270 comprises an exemplary Eat page, which 50 forms, including but not limited to, non-volatile media and may include navigation 1202, selected page 1204E, sync volatile media. Non-volatile media includes, for example, widget 1216, leaderboard elements 1240C and 1240D, sta­ optical or magnetic disks, such as disk drive 1310. Volatile tistics report engine 1254, comparison element 1242C, search media includes dynamic memory, such as system memory and recommendations element 1272, product sales element 1306. 1282, maps element 1280A, nutrition science element 1276, 55 Common forms of computer readable media includes, for and daily food/supplement element 1278. Navigation 1202, example, floppy disk, flexible disk, hard disk, magnetic tape, any other magnetic medium, CD-ROM, any other optical selected page 1204E, sync widget 1216, leaderboard ele­ ments 1240C and 1240D, statistics report engine 1254, com­ medium, punch cards, paper tape, any other physical medium parison element 1242C, search and recommendations ele­ with patterns of holes, RAM, PROM, EPROM, FLASHment 1272, product sales element 1282, and maps element 60 EPROM, any other memory chip or cartridge, or any other 1280A may be implemented as described above with regard medium from which a computer can read. to like-numbered or corresponding elements. The Eat page Instructions may further be transmitted or received using a may be implemented to include a nutrition science element transmission medium. The term"transmission medium" may 1276, which may display, or provide widgets for accessing, include any tangible or intangible medium that is capable of information associated with nutrition science. The Eat page 65 storing, encoding or carrying instructions for execution by the also may be implemented with a daily food/supplement ele­ machine, and includes digital or analog communications sig­ ment 1278, which may be implemented to suggest an food nals or other intangible medium to facilitate communication Case3:15-cv-02579 Document1-1 Filed06/10/15 Page56 of 64 US 8,446,275 B2 33 34 of such instructions. Transmission media includes coaxial tions. Examples of parameters include motion actions, such cables, copper wire, and fiber optics, including wires that as a step, stride, swim stroke, rowing stroke, bike pedal comprise bus 1302 for transmitting a computer data signal. stroke, and the like, depending on the activity in which a user In some examples, execution of the sequences of instruc­ is participating. As used herein, a motion action is a unit of tions may be performed by a single computer system 1300. 5 motion (e.g., a substantially repetitive motion) indicative of According to some examples, two or more computer systems either a single activity or a subset of activities and can be 1300 coupled by communication link 1320 (e.g., LAN, detected, for example, with one or more accelerometers and/ PSTN, or wireless network) may perform the sequence of or logic configured to determine an activity composed of instructions in coordination with one another. Computer sys­ specific motion actions. Activity manager 1432 cooperates tem 1300 may transmit and receive messages, data, and 10 with conversion module1420 to form a target activity score to instructions, including program, i.e., application code, which a user strives to attain. As such, activity manager1432 through communication link 1320 and communication inter­ is configured to track a user's progress and to motivate the face 1312. Received program code may be executed by pro­ user to modify anaerobic and/or aerobic activities to attain or match the activities defined by an optimal activity profile. cessor 1304 as it is received, and/or stored in disk drive 1310, or other non-volatile storage for later execution. 15 Activity manager 1432, therefore, is configured to coach a FIG. 14 depicts an example of an aggregation engine, user to improve the user's health and wellness by improving according to some examples. Diagram1400 depicts an aggre­ the user's physical activity, including primary activities of gation engine 1410 including one or more of the following: a exercise and incidental activities (e.g., walking and climbing sleep manager 1430, an activity manager 1432, a nutrition stairs in the home, work, etc.). According to various one or manager 1434, a general health/wellness manager 1436, and 20 more examples, activity-related parameters can be acquired a conversion module 1420. As described herein, aggregation or derived by any of the sensors or sensor functions described engine 1410 is configured to process data, such as data rep­ in, for example, FIGS. 3 to 5E. For example, other parameters resenting parameters based on sensor measurements or the (e.g., location-related parameters describing a gym location like, as well as derived parameters that can be derived (e.g., or social-related parameters describing proximity to other mathematically) based on data generated by one or more 25 persons working out) can be used to determine whether a user sensors. Aggregation engine 1410 also can be configured to is engaged in a movement-related activity, as well as the determine an aggregate value (or score) from which a graphi­ aspects thereof. cal representation or any other representation can be gener­ Nutrition manager 1434 is configured to receive data rep­ ated. Conversion module1420 is configured to convert data or resenting parameters relating to one or more activities relatscores representing parameters into values or scores indicat- 30 ing to nutrition intake of a user and to maintain data repreing relative states of sleep, activity, nutrition, or general fit­ senting one or more nutrition profiles. Nutrition-related ness or health (e.g., based on combined states of sleep, activ­ parameters describe characteristics, factors or attributes of ity, nutrition). Further, values or scores generated by consumable materials (e.g., food and drink), including nutri­ conversion module 1420 can be based on team achievements ents, such as vitamins, minerals, etc. that a user consumes. 35 Nutrition-related parameters also include calories. The nutri­ (e.g., one or more other users' sensor data or parameters). tion-related parameters can be formed from sensor data or Sleep manager 1430 is configured to receive data repre­ derived based on computations. In some cases, a user pro­ senting parameters relating to sleep activities of a user, and vides or initiates data retrieval representing the nutrition of configured to maintain data representing one or more sleep food and drink consumed. Nutrition-related parameters also profiles. Parameters describe characteristics, factors or attributes of, for example, sleep, and can be formed from 40 can be derived, such as calories burned or expended, sensor data or derived based on computations. Examples of Examples of parameters include an amount (e.g., expressed in parameters include a sleep start time (e.g., in terms of Coor­ international units, "lU") of a nutrient, such as a vitamin, dinated Universal. Time, "UTC," or Greenwich Mean Time), fiber, mineral, fat (various types), or a macro-nutrient, such as a sleep end time, and a duration of sleep, which is derived water, carbohydrate, and the like. Nutrition manager 1434 from determining the difference between the sleep end and 45 cooperates with conversion module 1420 to form a taiget start times. Sleep manager 1430 cooperates with conversion nutrition score to which a user strives to attain. As such, nutrition manager 1434 is configured to track a user's module 1420 to form a target sleep score to which a user strives to attain. As such, sleep manager 1430 is configured to progress and to motivate the user to modify dietary-related track a user's progress and to motivate the user to modify activities and consumption to attain an optimal nutrition prosleep patterns to attain an optimal sleep profile. Sleep man- 50 file. Nutrition manager1434, therefore, is configured to motiager 1430, therefore, is configured to coach a user to improve vate a user to improve the user's health and wellness by the user's health and wellness by improving the user's sleep improving the user's eating habits and nutrition. According to activity. According to various one or more examples, sleepvarious one or more examples, nutrition-related parameters can be acquired or derived by any of the sensors or sensor related parameters can be acquired or derived by any of the sensors or sensor functions described in, for example, FIGS. 55 functions described in, for example, FIGS. 3 to 5E. For 3 to 5E. For example, other parameters (e.g., location-related example, other parameters (e.g., location-related parameters parameters describing a home/bedroom location or socialidentifying the user is at a restaurant, or social-related param­ related parameters describing proximity with family mem­ eters describing proximity to others during meal times) can be bers) can be used to determine whether a user is engaged in a used to determine whether a user is engaged in a nutrition sleep-related activity and a quality or condition thereof. 60 intake-related activity as well the aspects thereof. In one Activity manager 1432 is configured to receive data repre­ example, acquired parameters include detected audio con­ senting parameters relating to one or more motion or move­ verted to text that describes the types of food or drink being ment-related activities of a user and to maintain data repre­ consumed. For example, a user in the restaurant may verbally senting one or more activity profiles. Activity-related convey an order to a server, such as "I will take the cooked parameters describe characteristics, factors or attributes of 65 beef, a crab appetizer and an ice tea." Logic can decode the motion or movements in which a user is engaged, and can be audio to perform voice recognition. Location data received established from sensor data or derived based on computafrom a sensor can be used to confirm the audio is detected in Case3:15-cv-02579 Document1-1 Filed06/10/15 Page57 of 64 US 8,446,275 B2 35 36 the context of a restaurant, whereby the logic determines that Conversion module 1420 includes a score generator 1422 the utterances likely constitute an order of food. This logic and an emphasis manager 1424. Score generator 1422 is can reside in nutrition manager 1434, which can be disposed configured to generate a sub-score, score or target score based in or distributed across any of a wearable computing device, on sleep-related parameters, activity-related parameters, and an application, a mobile device, a server, in the cloud, or any 5 nutrition-related parameters, or a combination thereof, other structure. Emphasis manger 1424 is configured emphasize one or more General health/wellness manager 1436 is configured to parameters of interest to draw a user's attention to addressing manage any aspect of a user's health or wellness in a manner a health-related goal. For example, a nutrition parameter indi­ similar to sleep manager 1430, activity manager 1432, and cating an amount of sodium consumed by a user can be nutrition manager 1434. For example, general health/well- 10 emphasized by weighting the amount of sodium such that it ness manager 1436 can be configured to manage electromag­ contributes, at least initially, to a relatively larger portion of a netic radiation exposure (e.g., in microsieverts), such as target score. As the user succeeds in attaining the goal of radiation generated by a mobile phone or any other device, reducing sodium, the amount of sodium and its contribution such as an airport body scanner. Also, general health/wellness to the taiget score can be deemphasized. manager 1436 can be configured to manage amounts or doses 15 Status manager 1450 includes a haptic engine 1452 and a of sunlight sufficient for vitamin D production while advising display engine1454. Flaptic engine 1452 can be configured to a user against an amount likely to cause damage to the skin. impart vibratory energy, for example, from a wearable device According to various embodiments, general health/wellness 1470 to a user's body, as a notification, reminder, or alert manager 1436 can be configured to perform or control any of relating to the progress or fulfillment of user's sleep, activity, the above-described managers or any generic managers (not 20 nutrition, or other health and wellness goals relative to taiget shown) configured to monitor, detect, or characterize, among scores. Display engine 1454 can be configured to generate a other things, any one or more acquired parameters for deter­ graphical representation on an interface, such as a touchmining a state or condition of any aspect of health and well­ sensitive screen on a mobile phone 1472. In various embodi­ ness that can be monitored for purposes of determining trend ments, elements of aggregation engine 1410 and elements of data and/or progress of an aspect of health and wellness of a 25 status manager 1450 can be disposed in either wearable user against a target value or score. As the user demonstrates device 1470 or mobile phone 1472, or can be distributed consistent improvement (or deficiencies) in meeting one or among device 1470, phone 1472 or any other device not more scores representing one or more health and wellness shown. Elements of aggregation engine 1410 and elements of scores, the target value or score can be modified dynamically status manager 1450 can be implemented in either hardware to motivate a user to continue toward a health and wellness 30 or software, or a combination thereof, goal, which can be custom-designed for a specific user. The FIG. 15A depicts an example of an aggregation engine including a general health and wellness manager configured dynamic modification of a target goal can also induce a user to operate with and/or control one or more managers, accord­ to overcome slow or deficient performance by recommending various activities or actions in which to engage to improve ing to some examples. Diagram 1500 depicts a sleep manager nutrition, sleep, movement, cardio goals, or any other health 35 1530, an activity manager 1532, a nutrition manager 1534, a and wellness objective. Further, a wearable device or any general health/wellness manager 1536, an environmental structure described herein can be configured to provide feed­ manager 1537, a social manager 1535, any number of generic back related to the progress of attaining a goal as well as to managers 1531a, and a conversion module 1520. Any of induce the user to engage in or refrain from certain activities. managers 1525, including general health/wellness manager Thefeedbackcanbegraphicalorhapticinnature,butisnotso 40 1536, can be implemented in hardware or software, or a combination thereof. For instance, a manager can be imple­ limiting. Thus, the feedback can be transmitted to the user in mented as downloadable executable instructions that can be any medium to be perceived by the user by any of the senses obtained via a on-line marketplace. In the example shown, of sight, auditory, touch, etc. general health/wellness manager 1536 is configured to assist, Therefore, that general health/wellness manager 1436 is not limited to controlling or facilitating sleep, activity and 45 facilitate and/or control operations of managers 1525 to nutrition as aspects of health and wellness, but can monitor, obtain acquired parametric for respective aspects of health and nutrition identified for monitoring, tracking and generat­ track and generate recommendations for health and wellness ing feedback. Any of managers 1525 can communicate data based on other acquired parameters, including those related to the environment, such as location, and social interactions, with any other manager 1525 to more readily detect actions, including proximity to others (e.g., other users wearing simi- 50 environments and socially-related events in which the use is engaged. For example, an environmental manager 1537 can lar wearable computing devices) and communications via determine and monitor locations, which can be used to deter­ phone, text or emails that can be analyzed to determine mine whether a user is at a restaurant (e.g., engaged in nutri­ whether a user is scheduling time with other persons for a specific activity (e.g., playing ice hockey, dining at a rela­ tion intake) or on a running track (e.g., engaged in exercise). An example of activity manager 1532 is disclosed in U.S. tive's house for the holidays, or joining colleagues for happy 55 hour). Furthermore, general health/wellness manager 1436 patent application Ser. No. 13/433,204 filed on Mar. 28,2012, and/or aggregator engine1410 is not limited to the examples which is hereby incorporated by reference for all purposes. An example of sleep manager 1530 is disclosed in U.S. patent described herein to generate scores, the relative weightings of activities, or by the various instances by which scores can be application Ser. 13/433,208 filed on Mar. 28, 2012, which is calculated. The use of points and values, as well as a use of a 60 hereby incorporated by reference for all purposes. An target score are just a few ways to implement the variety of example ofnutrition manager 1534 is disclosed in U.S. patent application Ser. No. 13/433,213 filed on Mar. 28,2012, which techniques and/or structures described herein. A target score can be a range of values or can be a function of any number of is hereby incorporated by reference for all purposes. Generic health and wellness representations. In some examples, spe­ manager(s) 1531a represents any number of hardware and/or cific point values and ways of calculating scores are described 65 software implementations configured to manage the acquisiherein for purposes of illustration and are not intended to be tion of acquired parameters for monitoring any aspect of limiting. health and wellness for purposes of, for example, tracking a Case3:15-cv-02579 Document1-1 Filed06/10/15 Page58 of 64 US 8,446,275 B2 37 38 tion describing interactions or future interactions with others. user's progress and improvements toward a goal for an aspect For example, social-related parameters can include data of health and wellness (e.g., limiting amounts of sun light, derived from phone calls (e.g., decoded audio and speech into limiting consumption of fish with known levels of mercury, text, caller ID information, date, time, etc.), emails, texts, and limiting exposure to electromagnetic radiation, and any other state or conditions that affect one's health). Further, generic 5 other communications in which a user is arranging an activity with other persons. Social-related parameters can also manager(s) 1531a facilitate score calculations relating to any include data from or exchanged with various networking web specific aspect of health and wellness and can provide rec­ sites in which users exchange information between one or ommendations for improving such scores. more levels of permissions (e.g., usually based on friendships Environmental manager 1537 is configured to receive data representing parameters relating to an environment in which 10 or as acquaintances). General health/wellness manager 1536 can use this information to generate recommendations on a user (or other persons of interest) is disposed, and config­ whether to associate with active persons rather than inactive ured to maintain data representing one or more environmental persons and to predict types of activities a user is engaged in profiles. Environment-related parameters describe character­ base on, at least in part, the information derived from comistics, factors or attributes of, for example, an environment, and can be formed from sensor data or derived based on 15 munications and interactions with others. Also, social manager 1538 is configured to generate recommendations to computations. In some examples, environment-related induce users to socialize with others with similar goals or to parameters canbe acquired or derived by any of the sensors or reinforce favorable habits (e.g., telling a person next to the sensor functions described in, for example, FIGS. 3 to 5E. user a good reasons to drink water). The above-described Examples of environmentally-related parameters include a location (e.g., absolute in terms of geometric coordinates via 20 examples are not intended to be limiting. GPS, or approximate coordinates based on triangulation of Conversion module 1520 includes a score generator 1522 radio signals, etc.), and perceptible aspects of an environ­ and an emphasis generator 1524, according to some ment, such as audio aspects (e.g., spoken words detectable to examples. The functionality and/or structure can be equiva­ determine certain activities related to nutrition intake, exerlent to similarly-named elements described herein. Score cise, etc.) or visual aspects. Examples of environmentally- 25 generator 1522 can include an activity-sleep-nutrition ("A/S/ related parameters also include data representing vibrations N") score generator 1540 configured to calculate one or more or motion that a wearable device is experiencing (e.g., the scores based on activity, sleep, nutrition-intake or any other user is traveling in a car), locations of identified friends or aspect of health and wellness for a user, and a context score users of other wearable computing devices in communication generator 1540 configured to calculate one or more scores with each other, locations of destinations or originations, 30 based on the environment and/or social interactions (or proxlocations of places to avoid (e.g., a food court in a mall) or to imities) between a user and other people. In some examples, migrate toward (e.g., another user that is participating in a context score generator 1540 generates a context score that similar activity), numbers of people on a jogging route (e.g., indicates a context in which a user is disposed or in which a user is performing an activity. The context score can be used to ensure an optimal running route), atmospheric pressures, whether the wearable device is submeiged in water, and any 35 to influence a score to provide motivation and inducements to other parameter that defines or describes an environment of a user to meet one or more health and wellness objectives, interest. Other environmentally-related parameters include responsive to environmental and social factors. data representing health and wellness characteristics of a FIG. 15B depicts an example of a flow to modify a taiget location (e.g., general health or characteristics of people vis­ score to enhance a general health and wellness of a user, iting a location), such as a stadium, restaurant, or a home, or 40 according to some examples. At 1552, parameters describing of a region (e.g., general health or characteristics of people any aspect of health and wellness is captured (i.e., acquired), living in a region, such as rates of alcoholism, obesity, etc. of and one or more scores are calculated at 1554 (e.g., a score a city, county or state). Such data can be used to influence can represent a user's ability to attain a targeted goal for one score calculations and/or recommendations. The above-deaspect of health and wellness, such as sleep, nutrition, etc.). scribed examples are not intended to be limiting. Environ- 45 At 1556, the one or more scores are aggregated to form an mental manager1537 is configured to also generate trend data overall health and wellness score, which can be compared relating to locations and other activities a user is engaged to against a target score indicative of an optimal state or condi­ predict a future activity (e.g., a dance class) that is possible tions of health and wellness for a user.At 1558, once require­ based on past visits to a location (e.g., a gym). ments are met to change the methods of calculating a taiget Social manager 1538 is configured to receive data repre- 50 score, the new taiget score is dynamically changed at 1560 senting parameters relating to social interactions and prox­ based on the user's progress or continued progress. In par­ imities to others relative to a user (or other persons of inter­ ticular, a determination is adjusted upon which to modify the est). In some examples, social-related parameters can be target score, the determination being based on, for example, a acquired or derived by any of the sensors or sensor functions calculation expressing activities in which a user is to engage described in, for example, FIGS. 3 to 5E, including mobile 55 to meet its health goals. In some cases, the requirements to change the calculations of a taiget score are based on the user phones and computing devices. Social-related parameters describe characteristics, factors or attributes of, for example, consistently attaining a certain level or overall score. The new a social network of a user, and can be formed from sensor data target score calculations ensure the user is motivated or or derived based on computations. Examples of social-related induced to continue to improve his or her health at least until parameters include data representing family and friends, and, 60 the taiget scoring is again modified.At 1562, modified activioptionally, aspects of their health and wellness, and data ties are implemented for the user. That is, the types and representing other users of wearable devices, and, optionally, amounts of an activity can be "leveled up," so that user is aspects oftheir health and wellness, too. For example, friends challenged further. The flow continues monitoring at 1564. 1, 4 and 7 can be identified from their health and wellness FIG. 16A depicts examples of a social manager and an profiles, overall scores or taigets scores to be active friends. 65 environmental manager configured to generate a context Examples of other social-related parameters include data rep­ score, according to some examples. Diagram 1600 shows a resenting proximities to other wearable devices and informauser 1602 at a location 1620 subject to its environment from Case3:15-cv-02579 Document1-1 Filed06/10/15 Page59 of 64 US 8,446,275 B2 39 40 which environmental parameters 1630 (e.g., location, ternperature, noise levels, atmospheric pressure, talking or speech levels, etc.) can be acquired. Further, social parameters 1640 can be acquired. Examples of social parameters 1640 include a number of people wearing wearable devices 1608 contemporaneously, in proximity to the user, and/or engaged in similar activities or movements. User 1602 (or accompanying devices) can be interacting in a manner with others to receive and/or exchange social parameters 1640 from a social network of friends 1642 have a certain level of authorization or permissions to interact with user 1602 (and/ or mobile devices 1604 and wearable device 1606). Persons described as friends may or may not include wearable devices 1608 as part of a social network based on networked wearable devices. In some cases, mobile devices 1604 and/or wearable device 1606 are configured to communicate with a larger subset of persons (e.g., a universe of users using wearable devices 1608 in networks 1644 and 1646). In some cases, nutrition parameters1632and/orphysical parameters1634of user 1602 (and other authorized users), or an overall score based on those and others parameters, can be exchanged one or more social networks 1642,1644, and 1646. Diagram 1600 also shows social manager 1538 and an environmental manager 1537 configured to exchange data with context score generator 1542. For example, social manager 1538 and environmental manager 1537 can transmit to context score generator1542 values of acquired environmental parameters 1630 and values of acquired social parameters 1640. Social manager 1538 and/or environmental manager 1537, as well as general health/wellness manager 1536, can be configured to facilitate social networks and the functionalities and/or structures are described in FIGS. 12A to 12F. Context score generator 1542 generates a context score that is indicative ofthe degree of impact caused by either an aspect of the environment or social interactions, or both, in relation to user 1602. For example, a context score can be negatively impacted if user 1602 lives or spends time in regions of high rates of obesity, or with a group of people that tend to be sedentary, or at bars and nightclubs. However, the context score can be positively influenced by spending time at or near areas of relatively high occurrences of physical activities (e.g., spending time on a basketball court) or having a network of active friends. The context score is provided to general health and wellness manager 1536 to optionally influence an overall score (e.g., including sleep, nutrition and activity scores) relative to a target score. Responsive to a context score, general health and wellness manager 1536 can generate recommendations. For example, general health and wellness manager 1536 can determine that a user is at a specific locationandcanrecommendoneormoreactivitiesassociated with that location or a structure at that location. If user 1602 is ata stadium, general health and wellness manager1536 can generate recommendations to climb a number of stairs associated with the stadium structure, or can suggest a glass of water rather than a beer with a hot dog. If user 1602 is at a shopping mall, mobile devices 1604 and/or wearable device 1606 can project a path 1622 that passes a food court and recommend altering course onto another path 1624 to avoid the food court or to connect socially with another user sharing, for example, similar health and wellness profiles (i.e., goals). Therefore, general health and wellness manager 1536 can generate recommendations based on acquired parameters received by any sleep manager, activity manager, nutrition manager, environmental manager, social manager, or any number of generic managers to determine an overall score relative to an overall target score and can propose actions that affect oneaspect of health, and wellness (e.g., sleeping) based on one or more other aspects of health and wellness (e.g., environment, nutrition, etc.). In some embodiments, wearable device 1606 can generate messages encoded in vibratory messaging. For example, two long vibratory pulses can indicate that user 1602 ought to turn right and three short vibratory pulses can indicate that a user 1602 turn left. This vibratory messaging scheme can assist navigation of user 1602 to avoid detrimental locations, such as a food court, or can assist user to select a less populous running route based on data originating from a server that describes a number of pedestrians and cyclists based on loca­ tions of other wearable devices 1606 or cell phone locations (e.g., base on triangulation, GPS, or other means). The vibratory energy can increase as the user 1602 comes closer to a point at which to turn and decreases once the user passes that point. FIG. 16B is an example flow diagram 1650 to determine recommendations based on a context score to manage health and wellness, according to some examples. At 1652, data representing one or more location-related reference param­ eters are received. For example, the one or more locationrelated reference parameters can include data representing what structures exist at the location and what activities typically occur there. At 1654, acquired parameters associated with the location of a user are obtained. Optionally, data representing one or more social-related reference parameters are received at 1653. For example, the one or more socialrelated reference parameters can include data representing the degree to which one or more friends, colleagues or people areactiveorparticipateinsimilaractivities.Atl655,acquired parameters associated with the social participation of a user are obtained. At 1656, one or more scores are calculated relative to reference parameters. For example, positive values may be used in calculations when a user is interacting with active people, and negative values may be used when a user spends more than a certain amount of time at a bar or sitting at a location in front of a television. Scores can be adjusted optionally at 1658 to emphasize or deemphasize either positive actions or detrimental actions of a user. At 1660, scores are combined to determine an overall score that represents the overall heath and wellness of one or more users. That is, an overall score can be based on a single user or a group of users, whereby those in the group are linked together to induce encouragement in achieving health and wellness goals. At 1662, data signals representing one or more scores are generated to present to a user, for example, via visual means, such as a display, or haptic means, such as vibratory energy. Feedback can be determined at 1664 based on context score, and one or more proposals incorporating the feedback can be embodied in data signals at 1666 to propose actions for improving one or more scores. A determination whether to implement the feedback is made at 1670. If it is, then flow 1650 continues to monitor acquired parameters and calculating scores to determine, if applicable, to dynamically change the taiget score to reflect the user's improvements and to further incentivize or motivate the user. FIGS. 16C and 16D depict examples of displays including feedback based on environmental or social parameters, according to some examples. In FIG. 16C, a display 1680 of a mobile device can depict a target score 1682 and a recommendation 1686 based on social parameters to encourage the user to alter score 1684 to meet target score 1682. In FIG. 16D, a display 1690 of a mobile device can depict a taiget score 1692 and a recommendation 1694 based on environmental parameters to encourage the user to achieve taiget score 1692. Note displays are not limited to displays1680 and 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-1 Filed06/10/15 Page60 of 64 US 8,446,275 B2 41 42 skin galvanization, average skin galvanization, instantaneous 1690 and can be disposed on a wearable device and can heart rate, average heart rate, instantaneous perspiration, convey information via different media other than visual average perspiration, instantaneous blood sugar level, aver­ (e.g., auditory, perceptible by touch, etc.). age blood sugar level, instantaneous respiration rate, average FIG. 11A depicts an example of a general health and well­ ness manager, according to some examples. Diagram 1700 5 respiration rate, and the like, Examples of nutrition parameters 1714 include types of depicts general health and Wellness 1536 including one or consumable materials and their nutrient compositions for more of the following: a data interface 1701, a health and specific unit amounts or volume. As used herein, the term wellness evaluator 1702, a manager coordinator 1706, a "consumable material" refers to any material consumed as repository 1703 configured to store data representing trend or archival data files 1713, a repository 1707 configured to store 10 either food or drink and has at least oneor more nutrients from which to provide a user. A consumable material can be medi­ data representing one or more profiles 1709, and a profile cine or any other substance that enters the body (e.g., orally or generator 1710. A bus 1705 couples each of the elements for by any other means, such as through the skin or is inhaled). A purposes of communication. Profile generator 1710 can gen­ "consumable material component" is a component of a meal, erate one or more profiles representativeof a user's patterns of various activities associated with certain aspects of health and 15 such as a side salad, French fries, or a main entree, that, when combined with other meal components, form a meal. Each of wellness based on trend analysis (e.g., empirically over time and various cycles of meals, sleep, time at certain locations, the consumable material components can have equivalent social interactions, and the like. A profile for a user can be nutrients, such as sodium, that can be isolated, measured, input or entered via data 1720 to establish an initial over monitored and reported as an aggregate amount of the specific health and wellness profile based on one or more aspects 20 nutrient for the meal (i.e., over all the parts of the meal containing that nutrient). In some embodiments, nutrition thereof. Profile generator 1710 can generate data representing parameters 1714 can be stored as nutrition parameter data a subset of acquired parameters to establish a baseline profile 1713. Types of consumable materials include unprocessed against which a user's progress canbe measured in modifying foods and drink, such as fruits, vegetables, unprocessed behavior when working toward a goal (e.g., overall target score) that is consistent with a healthy lifestyle. For example, 25 meats, water, etc., and processed foods and drink, such as restaurant meals, processed and packaged foods, etc. Nutri­ the profile generated by profile generator 1710 can represent tion parameters 1714 can include descriptors specifying a daily average of activities affectingvarious aspects of health amounts of the nutrients, such as units (e.g., real numbers and wellness over one or more days during which acquired representing units of measure, such as IUS, mg, g, ml, cups, parameters were used to determine the trends for a user. Or, the profile generated by profile generator 1710 can represent 30 etc.), and types of nutrients. Types of nutrients can include carbohydrates (of a various subtypes, including fiber), fats, a current interval of time (e.g., a specific day) in which an minerals, proteins, vitamins, water, and any combination or aspect of a user's health and wellness is monitored, and variation thereof. Data representing nutrition parameters can optionally modified to conform the user's behavior to a set of be acquired (e.g., as acquired parameters) by way of input by behaviors associated with a taiget score, which can be deter35 a user. A social parameter includes data representing a social mined by a profile 1709. interaction between a user and another person via any form of Data interface1701 is configured to receive data represent­ communication, such as face-to-face, phone, email, text, ing parameters, such as physical parameters 1711, environ­ amounts of time spent with a person, and the like. Social mental parameters1712, andnutrition parameters1714. Such parameters can be archived in archived data files 1713 so that parameters can originate at any type of sensor, such as those described herein, or can be derived (e.g., computationally), or 40 trends can be established to determine, for example, the can be input as data extracted, for example, from a networked people with which a user tends to participate in positive database. Examples of physical parameters 1711 include a activities (i.e., in terms of achieving a target score). This sleep start time, a sleep end time, a duration of light sleep information can be used to generate recommendations to (and/or a total duration of light sleep between the start and induce a user toward achieving a taiget score. Any other sleep end times), a duration of deep sleep (and/or a total 45 characteristics of social interactions, including proximity to duration of deep sleep between the start and sleep end times), other persons (or the proximities of wearable devices relative a heart rate, a body temperature, and the like. Examples of to each other) and data derived from social networking web environmental parameters 1712 include an amount of light, a sites and other databases are also included in social param­ level of sound eneigy, an ambient temperature, a location of a eters 1716. As used herein, the term "acquired parameter" user, a location of another user, and the like. Environmental 50 refers to one or more parameters that are obtained for purparameters, as well as any other parameter, can be archived in poses of analyzing nutritional intake (e.g., nutrition param­ archived data files 1713 so that trends can be established to eters describing nutrition of food or drink that is consumed or determine, for example, the locations at which a user tends to to be consumed). Data representing an acquired parameter participate in positive activities (i.e., in terms of achieving a can include an amount (e.g., units) of a nutrient and a type of target score). This information can be used to generate rec- 55 the nutrient. In some embodiments, an acquired parameter is ommendations to induce a user toward achieving a target associated with data originating from a wearable computing score. Parameters also can include nutrient-related param­ device. In some embodiments, nutrition parameters 1714 can eters that causes physiological manifestations in, for be retrieved from repository 1703 or over a network from a example, types of gases, such as C02 expelled from the lungs remote database. For example, a restaurant or food producer or skin, as well as steps, minutes of activity/motion, minutes 60 may provide access to nutrition data in a remote database that of inactivity/no motion, intensity of activity, aerobic minutes, is accessible by customers for purposes of evaluating nutri­ tion for health and wellness. In at least some examples, nutri­ aerobic intensity, calories burned, training sessions, length, of training sessions, intensity of training sessions, calories tion parameters 1714 can be determined via image capture burned during training session(s), type of activities, duration with image recognition logic and/or user input. An example of each type of activity, intensity of each type of activity, 65 of the use of image recognition logic is shown in FIG. 17B. calories burned during each type of activity, instantaneous Health and wellness evaluator 1702 is configured to body temperature, average body temperature, instantaneous acquire data representing acquired parameters describing the Case3:15-cv-02579 Document1-1 Filed06/10/15 Page61 of 64 US 8,446,275 B2 43 44 fulness, a sleep start time, a sleep end time, a body tempera­ various aspects of health and wellness of a user, including, but ture, an ambient temperature, an amount of light, an amount not limited to, nutrition-related characteristics, sleep-related of sound energy, a unit and type of one or more consumable characteristics, movement-related characteristics, environ­ materials (e.g., food and/or drink), an indication of particimental characteristics, social-related characteristics, among others. In particular, health and wellness evaluator 1702 is 5 pating in an activity with other users, etc. Scores are calculated at 1756 relative to or associated with configured to determine characteristics of an activity, state or baseline parameters, whichcan be associated with a reference condition for a user. Health and wellness evaluator 1702 is further configured to identify the a specific activity and type value. For example, data representing values (e.g., points) for of activity (e.g., type of sleep, movement, nutritional intake, one or more subsets of acquired parameters (e.g., data via etc.) and generate data representing the units and types of the 10 measurement, sensor, derivation, etc.) are determined based activities for specific aspects of health and wellness. In some on reference values, such as a total number of points, for examples, health and wellness evaluator1702 is configuredto parameters set forth in the profile. For example, a user may set control manager coordinator 1706, which, in turn, is config­ as its goal to consume 45 milligrams of vitamin C per day (per World Health Organization standards). At breakfast, the user ured to facilitate, assist with or control operations of various managers, as well as interactions between the managers. The 15 consumes a meal and receives about 22 milligrams. A profile managers can operate cooperatively to tune or modify the includes data that equates 45 milligrams as 20 points (i.e., a interrelationships between multiple behaviors or activities of target score for this nutrient). In this case, 20 points is a a user to maximize various aspects of health and wellness. For reference value (i.e., the baseline parameter). As 22 milli­ example, manager coordinator 1706 can cause generation of grams, which represents an acquired parameter (e.g., units of: recommendations to improve one or more scores of the same 20 22 mg, and type of: vitamin C nutrient), is approximately half of the goal, the user receives 10 points as the value. Scores can or different aspects of health and wellness. Exemplary opera­ be calculated at a first processor based on data representing tion of manager coordinator 1706 is described by way of the values, whereby the score representing an attained portion several examples of tuning the interrelationships between of the one or more health-related activities. That is, a score multiple behaviors and activities of a user, as described in FIGS. 18A to 18D. 25 can be determined as an "overall score" to include one or In some embodiments, health and wellness evaluator1702 more of nutrition scores, sleep scores, activity scores, context also is configured to compare a user's profile (i.e., trend data scores or any other score, and the like. The overall score is representing aspects of health and wellness of a user) against indicative of an ability of a user to achieve a targeted level of data representing one or more health and wellness deficiency health and wellness and can represent the user's progress, for profiles 1708 to determine whether a deficiency exists (e.g., 30 example, on a daily basis in meeting a target score. The an irregular eating schedule, a lack of proper hydration, overall score can be express as a percentage of the taiget whether a nutrient deficit exists, whether a user spends score, such as 71% with 100 points set as the target score. extraordinary time in the ice cream isle of a supermarket, At 1758, at least one score can be adjusted toward or away etc.). As described above, manager coordinator 1706 is con­ from the target score. For example, if the user is agrees to figured to provide recommendations to modify the user's 35 spend time with active friends, then the user is awarded posibehavior to optimize one or more scores, including an overall tive points to encourage socializing with people more likely score, thereby optimizing the various user activities to facili­ to assist the user in reaching its health and wellness goals. But tate improved health and wellness. Health and wellness if a user spends a certain amount of time at a bar or in the evaluator 1702 can generate notifications and alerts (e.g., dessert isle of a supermarket, then points are deducted from graphical, haptic, audio, or otherwise perceptible to a user) to 40 its overall score to encourage the user to avoid tempting induce a user to modify user behavior, or environmental, locations. At 1760, a decision is made as to whether to imple­ social, nutritional, and/or physical parameters to improve a ment feedback. If so, flow 1750 moves to 1762, at which user's health. For example, a wearable device can vibrate to characteristics of health and wellness are identified for modi­ notify a user that a meal ought to be consumed at a certain fication to uige the user to improve scores, which, in turn, time, or a certain movement ought to be performed. In some 45 represents improved health. At 1766, the modifications are examples, health and wellness evaluator1702 is configuredto implemented. cause generation of a graphical representation on an interface At 1764, the determination of a score can be modified to induce modification of an acquired parameter, or to cause relative to a threshold. For example, when the overall score exceeds thetarget score, the rate at which the overall score can generation of a haptic-related signal for providing vibratory feedback to induce modification of the acquired parameter. 50 be reduced as a function of the difference between the overall FIG. 17B is an example flow diagram for a technique of score and the target score. That is, it gets more difficult to managing overall health and wellness using, for example, accrue points for the overall score when exceeding the taiget wearable devices that include sensors, according to some score. For example, for overall scores between 100 and 110, examples. At 1752, data representing one or more baseline it is 50% harderto obtain overall score points (e.g., 25% fewer parameters is received. The baseline parameters can include 55 points are rewarded), for overall scores between 111 and 125, any health-related characteristics that define parameters upon it is 75% harder to obtain overall score points, and for overall which a target score is established. Further, the target score scores above 126 it is 100% harder. At 1768, a classification can be established based on one or more health-related activifor a user can be either leveled up or down. For example, a ties. For instance, the baseline parameters can be set forth in subset of overall scores can be determined and the classificaa data arrangement constituting a profile 1709 of FIG. 17B. In 60 tion associated with a user can be changed based on the subset some cases, the values of the baseline parameters are such that of overall scores. The classification can be changed by level­ if the user attains or fulfils the goals of optimizing one or more ing up to a first health and wellness profile if the subset of aspects of health and wellness, the target score having a value overall scores is associated with a first range, or the classifi­ of 100. At 1754, parameters are acquired that describe a state cation can be changed by leveling down to a second health or characteristics of a user's activity. Examples of acquired 65 and wellness profile if the subset of overall scores is associparameters can include—via derivation or measurement—a ated with a second range. The first range of activity scores are heart rate, a duration of sleep, a location, a duration of wakenearer to the target score than the second range of activity Case3:15-cv-02579 Document1-1 Filed06/10/15 Page62 of 64 US 8,446,275 B2 45 46 scores. To illustrate, if the overall score is 95% of the target within time 1820. Further, manager coordinator 1706 or score (e.g., for a duration), the user is either leveled up or health and wellness evaluator 1702 can be configured to rec­ provided the opportunity to level up to implement, for ommend to engage in exercise no later than an amount of time example, a new value of a parameter of a different health and 1822 before bedtime. Positive points can be awarded if the wellness profile. But if the sleep score is 70% or less of the 5 user runs 1818 before time 1822. Negative points may be target score, the user is given the option to level down (e.g., to applied if the user runs 1818 during time 1812, as sleep likely a less ambitious or rigorous health and wellness profile). In is to be affected by exercising so close to sleep time. this manner, the target score is dynamically altered just FIG. 18C depicts data 1830 representing activity and data beyond the current limitations of the user to induce or other­ 1850 representing nutrition relative to time, whereby the data wise motivate the user to work harder and strive to attain the 10 can represent instantaneous (e.g., in real or near real time) new target score, and, ultimately, a healthy lifestyle. At 1770, activity data and nutrition data, or data 1830 and 1850 can flow 1750 determines whether to continue monitoring and represent archived or trend data, or projected activity occur­ ring typically at different times during a day. Activity man­ moves to 1772 to do so. At 1772, other parameters are acquired and further monitoring is performed. Note that more ager 1532 and nutrition manager 1530 cooperate to modify or less blocks, elements, actions or steps of flow 1750 can be 15 one aspect of healthand wellness, such as activity, to optimize implemented, and note further that flow 1750 is not intended another aspect, such as sleep. For example, activity manager to be limiting. 1530 can determine instantaneous or predicted states of FIGS. 18A to 18D depict interrelationships between dif­ movement for a user, such as a workout activity 1840 (e.g., a ferent aspects of health and wellness and different managers marathon), and nutrition manager 1532 can be used to reccooperating to optimize the same, according to various 20 ommend times at which user consumes different foods or drink prior to working out. In operation, manager coordinator examples. FIG. 18A depicts data 1802 representing sleep and 1706 or health and wellness evaluator1702 can be configured data 1804 representing nutrition-intake activity relative to to propose a time or duration 1832 in which a user is recom­ time, whereby the data can represent instantaneous (e.g., in mended to consume fresh fruit, bagels, energy bars, pasta, and real or near real time) sleep data and nutrition data, or data 1802 and 1804 can represent archived or trend data, or pro- 25 other like types of food 1852 (e.g., 3 to 5 hours before a competition). But during the time orduration 1834, the user is jected activity occurring typically at different times during a day. Sleep manager 1530 and nutrition manager 1534 coop­ advised to consume fresh fruits, bagels, water, and like con­ erate to modify one aspect of health and wellness, such as sumables 1854 (e.g., 2 to 3 hours before the competition), whereas the user is advised to consume specific fruits, such as nutrition, to optimize another aspect. For example, sleep manager 1530 can determine instantaneous or predicted 30 watermelon and oranges, limited amounts of sport drink and like consumables 1856 during time or duration 1836 (e.g., 1 states of wakefulness and sleep for a user, and nutrition man­ hour or less before competition). In various embodiments, ager 1534 can determine or predict nutrition intake as break­ activity manager 1532 and nutrition manager 1530 can coop­ fast 1806, lunch 1807, and dinner 1808. In some cases, either manager coordinator 1706 or health and wellness evaluator erate to improve the overall health and wellness of a user 1702, or both, can control sleep manager 1530 and nutrition 35 based on the interplay between movement and nutrition. As manager 1534. In operation, manager coordinator 1706 or such, the above-described is but one example. Positive can be health and wellness evaluator 1702 can be configured to pro­ awarded specific foods are consumed at the appropriate pose a time or duration 1810 in which a user is recommended times. to have breakfast 1806 after waking up. Positive or no points FIG. 18D depicts data 1860 representing location, data can be awarded if this meal occurs during interval 1810, and 40 1864 representing social interactions or proximity relative to negative points can be applied if the user fails to eat breakfast. time, data 1868 and 1869 representing environmental param­ Further, manager coordinator 1706 or health and wellness eters including audio, and data 1880 and 1881 representing evaluator 1702 can be configured to recommend to a user to movement relative to time. The data shown can represent have dinner no later than an amount of time 1812 before instantaneous activity data, social data, environmental data bedtime. Positive points canbe awarded if dinner1808 occurs 45 and activity data, or any of the data can represent archived or before time 1812 or include a meal conducive to enhance trend data, or projected activity occurring typically at differ­ sleep, such as foods with tryptophan. Negative points may be ent times during a day. In the example shown, environmental applied if caffeine or other stimulants are consumed during manager 1537, social manager 1538, and environmental man­ time 1812. ager 1537 are configured to assist activity manager 1532 in FIG. 18B depicts data 1802 representing sleep and data 50 determining the type of activity a user is engaged. As shown, 1814 representing activity relative to time, whereby the data environmental manager 1537 can determine locations of a can represent instantaneous (e.g., in real or near real time) user at different times of the times, such as at home 1861, at sleep data and activity data, or data 1802 and 1804 can rep­ work 1862, and at a gym 1863. Social manager 1538 is resent archived or trend data, or projected activity occurring configured to determine that user associated with colleagues typically at different times during a day. Sleep manager 1530 55 1865 during a first time period, with other persons 1866 and activity manager 1532 cooperate to modify one aspect of during a second time period, and family 1867 later on in the health and wellness, such as activity, to optimize another day. Environmental manager 1537 is configured to detect aspect, such as sleep. For example, sleep manager 1530 can voiced words1868, such as "walk" and "lunch," and further to determine instantaneous or predicted states of wakefulness detect voiced works 1869, such as "yoga" and "Fred."During and sleep for a user, and activity manager1532 can determine 60 the first time period, activity manager 1532 detects motion, and uses information that the person is at work, is associating or predict times at which user engages in walking 1816 and running 1818. In operation, manager coordinator 1706 or with colleagues and is in an environment in which speech is health and wellness evaluator 1702 can be configured to pro­ detected to conclude that the user is likely walking with colleagues to lunch. As such, activity ("1") 1880 is deterpose a time or duration 1820 in which a user is recommended to take a walk after waking up to take advantage of the most 65 mined to be walking. During the second time period, activity manager 1532 detects another type of motion, and uses infor­ energetic part of the user's day or circadian rhythm. Positive mation that the person is at a gym, is associating with other or no points can be awarded if this activity is performed Case3:15-cv-02579 Document1-1 Filed06/10/15 Page63 of 64 US 8,446,275 B2 47 48 a fifth persons (e.g., wearing similar wearable devices and partici­ pating in similar motions) and is in an environment in which social-related activities. speech is detected to conclude that the user is likely partici­ pating in a yoga class. As such, activity ("2") 7. The method of claim 6, wherein calculating the score 1882 is deter­ mined to be yoga. Note that the above-described examples are subset of acquired parameters associated with based on the data representing the values comprises: 5 not intended to be limiting, but rather to provide examples of generating a context score based on the fourth and fifth subsets of acquired parameters; and the various functionalities and/or structures that can be used aggregating the score and the context score to form the to manage a user's overall health and wellness by optimizing target score. one aspect of health and wellness to improve another, and to use acquired parameters (e.g., location, social interactions/ 10 proximities, etc.) to determine an activity in which a user is 8. The method of claim 1, further comprising: adjusting the score for one or more of the values to form an adjusted score; and participating. An ordinarily skilled artisan ought to appreciate using the adjusted score to form an overall score. that many different implementations disclosed herein that can 9. The method of claim 8, further comprising: be modified to address any aspect of managing user health by motivating the user to challenge oneself to meet its health 15 determining a context score based on either one or more location-related parameters or one or more social-re­ goals. lated parameters; and Although the foregoing examples have been described in some detail for purposes of clarity of understanding, the forming the adjusted score using the context score. above-described inventive techniques are not limited to the 10. The method of claim 1, further comprising: details provided. There are many alternative ways of imple- 20 determining a magnitude of a difference between the score and the target score; menting the above-described invention techniques. The dis­ closed examples are illustrative and not restrictive. predicting a subset of the acquired parameters to reduce the difference between the score and the target score; and generating data representing a recommendation to present What is claimed: 1. A method comprising: 25 to a user to engage in engage in a health-related activity. 11. The method of claim 10, wherein generating the data receiving data representing a profile defining parameters representing the recommendation comprises: upon which a target score is established based on one or generating data representing a suggestion to interact more health-related activities; socially with a subset of people who are associated with acquiring data representing one or more subsets of acquired parameters based on one or more sensors dis- 30 activity scores indicative of active users; and causing presentation of the suggestion to contact interact posed in a wearable computing device; with the subset of people to reduce the difference determining data representing values for the one or more between the score and the taiget score. subsets of the acquired parameters based on reference 12. The method of claim 10, wherein generating the data values for the parameters set forth in the profile; calculating at a first processor a score based on data repre- 35 representing the recommendation comprises: senting the values, the score representing an attained generating data representing a suggestion to interact physi­ portion of the one or more health-related activities; cally with a structure associated with a location of the causing presentation of a representation of the score rela­ user; and tive to the target score; and causing presentation of the suggestion to physically inter­ adjusting a determination upon which to modify the target 40 13. The method of claim 1, wherein acquiring data repre­ wherein the taiget score is indicative of one or more stan­ senting the acquired parameters comprises: dards against which to compare one or more groups of obtaining for an acquired parameter data representing a the values aggregated to form the score. 2. The method of claim 1, wherein the score is indicative of 45 wellness associated with the target score. method of claim 1, wherein the first senting the profile comprises: processor is obtaining data representing a value per unit of a parameter disposed in the wearable computing device. 4. The method of claim 1, wherein the one or more subsets and a reference value representing a target number of 50 of acquired parameters comprises: eter. 15. The method of claim 1, further comprising: subset of acquired parameters associated with sleep-related activities, causing generation of a graphical representation on an a second subset of acquired parameters associated with 55 nutrition-related activities, and causing generation of a haptic signal for providing vibra­ movement-related activities. of claim 4, wherein tory feedback to induce modification of the values for at least one subset of the acquired parameters. calculating the score based on the data representing the values comprises: 60 scores, the trend data being stored in a memory; and an activity score. 6. The method of claim 1, wherein the one or more subsets identifying at least one acquired parameter as deviating by a threshold amount from a corresponding parameter of acquired parameters comprises: data representing one or more of a fourth subset of acquired parameters associated with 16. The method of claim 1, further comprising: determining trend data representing one or more calculated aggregating one or more of a sleep score, a nutrition score location-related activities, and interface to induce modification of the values for at least one subset of the acquired parameters or a third subset of acquired parameters associated with 5. The method units of the parameter, wherein the parameter corresponds to the acquired param­ data representing one or more of a first type of parameter and units of the acquired parameter. 14. The method of claim 13, wherein receiving data repre­ an ability of a user to achieve a targeted level of health and 3. The act with the structure to reduce the difference between the score and the taiget score. score, 65 defined by the profile; recommending modification of the at least one acquired parameter to reduce the threshold amount; and Case3:15-cv-02579 Document1-1 Filed06/10/15 Page64 of 64 US 8,446,275 B2 49 detecting whether the at least one acquired parameter is modified. 17. The method of claim 1, further comprising: detecting the score exceeds the target score; and reducing a rate at which the score as a function of the difference between the score and the target score. 18. The method of claim 1, further comprising: determining a subset of scores; changing a classification associated with a user based on the subset of scores, wherein changing the classification including leveling up to a first classification or leveling down to a second classification. 19. A device comprising: a first interface configured to receive data representing acquired parameters from one or more sensors, at least one sensor being disposed in a wearable computing device; an aggregation engine comprising: a repository configured to store data representing a pro­ file defining parameters upon which a target score is established; and 50 5 10 15 20 one or more managers including one or more processors, at least one manager being configured to receive data representing a subset of the acquired parameters and further configured to determine data representing val­ ues for the subset of the acquired parameters, the values representing a point value relative to reference values for the parameters set forth in the profile; a score generator configured to: calculate a score based on data representing the val­ ues; and adjust the score based on threshold amounts for one or more of the values to form an adjusted score; a general health and wellness module configured to facilitate modification of a value of an acquired parameter associated with a state of a user to change the target score; and a status manager configured to cause presentation of a representation of the target score, wherein the score is indicative of relative proximity to the target score. Documentl-Z Filed06/10/15 Pagel of 28 Exhibit Case3:15-cv-02579 Document1-2 Filed06/10/15 Page2 of 28 US008073707B2 (12) (54) United States Patent (io) Patent No.: Teller et al. (45) (75) Inventors: Eric Teller, Pittsburgh, PA (US); John M. Stivoric, Pittsburgh, PA (US); Christopher D. Kasabach, Pittsburgh, PA (US); Christopher D. Pacione, Pittsburgh, PA (US); John L. Moss, Monroeville, PA (US); Craig B. Liden, Sewickley, PA (US); Margaret A. McCormack, Pittsburgh, PA (US) (73) Assignee: BodyMedia, Inc., Pittsburgh, PA (US) (*) Notice: U.S. PATENT DOCUMENTS (22) Filed: 19911766 Al 9/2000 OTHER PUBLICATIONS "Polar M91ti Heart Rate Monitor User's Manual", M91ticov.USA, (Nov. 13, 2000), 33 pages. (Continued) Primary Examiner — Gerald J. O'Connor Assistant Examiner — Natalie A Pass (74) Attorney, Agent, or Firm —GTC Law Group LLP & Affiliates; John A. Monocello, III Feb. 9, 2006 Related U.S. Application Data (63) Continuation of application No. 09/595,660, filed on Jun. 16, 2000, now Pat. No. 7,689,437. (51) Int. CI. G06Q 50/00 (2006.01) U.S. CI 705/2; 600/300 Field of Classification Search 600/300, 600/301, 365, 500, 509, 549; 705/2, 3, 1 See application file for complete search history. (52) (58) Raggiotti et al. Scheir et al. Lester etal. Mull Lester Lipsey Sassi et al. Wada Steueretal. Simbruner et al. Ward Reinhold, Jr. et al. Baumbach et al. (Continued) Prior Publication Data US 2006/0031102 Al 6/1977 10/1977 12/1978 4/1979 5/1979 3/1980 12/1982 3/1983 10/1983 12/1984 4/1985 7/1985 9/1985 FOREIGN PATENT DOCUMENTS DE Oct. 11, 2005 (65) A A A A A A A A A A A A A (Continued) This patent is subject to a terminal dis­ claimer. Appl.No.: 11/247,049 References Cited 4,031,365 4,052,979 4,129,125 4,148,304 4,151,831 4,192,000 4,364,398 4,377,171 4,407,295 4,488,558 4,509,531 4,531,527 4,539,994 Subject to any disclaimer, the term of this patent is extended or adjusted under 35 U.S.C. 154(b) by 1304 days. (21) US 8,073,707 B2 Date of Patent: *Dec. 6, 2011 (56) SYSTEM FOR DETECTING, MONITORING, AND REPORTING AN INDIVIDUAL'S PHYSIOLOGICAL OR CONTEXTUAL STATUS ABSTRACT (57) The invention is a system for detecting, monitoring, and reporting an individual's physiological or contextual status. The system works deriving a physiological or contextual status parameter of an individual using the system. The deri­ vation utilizes two sensed parameters of the individual. The system is able to present the derived parameter in relation to any other sensed parameters, entered information, life activi­ ties data, or other derived data. 24 Claims, 11 Drawing Sheets 55 ^-150 Local Telco Wireless Device •S 65 60 50-. ® • os • & Telco Computer g % Your Health Manager ^-155 ,5\ Your Health Index ^ 30 40 Xl • The Internet k5 User Location Oaily Dose excellent Very Good y. 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Response filed with the European Patent Office on Jul. 4, 2011 in European Patent Application No. 05077625.1. 35 40 10 50 I S/ Sensor Device Wireless Device 45 CD User Location FIG. 1 r •s J "I 5 The Internet 60 Telco Computer Local Telco Central Monitoring Unit 65 55 30 C/2 K> W ^1 O ^1 s* o 00 d o fD ft cr 5/3 K> O o\ n O ss P n C/5 Case3:15-cv-02579 Document1-2 Filed06/10/15 Page6 of 28 FIG. 2 Sensor I 12 Amplifier x 14 Conditioning Circuit £ 16 A/D Converter I 18 <" 24 I/O '' Memory Microprocessor 22 I / 20 • • 10 • SZ2 K> W ^1 o ^1 O 00 d O K> re re ST 5/3 K> o o\ o p n S3 £ C/5 Case3:15-cv-02579 Document1-2 Filed06/10/15 Page7 of 28 FIG. 3 CSU/DSU I 70 Router 1 75 Firewall [ 80 Network Storage r Database Server Switch L 110 100 85 L/" 190 Load Balancer 115 Server Middleware if Server J Middleware Server S Middleware 95c 95b 95a cr C/2 K> W ^1 o s* ^1 o 00 d o CD fD 5/3 o K> o\ CD e ss p C/5 Case3:15-cv-02579 Document1-2 Filed06/10/15 Page8 of 28 FIG. 4 CSU/DSU i 70 Network Storage I 100 J 110 Firewall £ Database Server Router i 75 130 Middleware Server 135a 80 a if 115 Switch Load Balancer Middleware Server Mirror Network Storage £ 120 J 90 135c 125 Load Balancer Middleware Server Database Server 85 135b a ir 122 Middleware Server Middleware Server Middleware Server if J $ 95c 95b 95a Xfl W <1 o <1 s* <1 o 00 s* d o fD ft cr 5/3 O K> o\ O ft P n SS Xfl Case3:15-cv-02579 Document1-2 Filed06/10/15 Page9 of 28 Case3:15-cv-02579 Document1-2 Filed06/10/15 Page10 of 28 U.S. Patent Dec. 6,2011 US 8,073,707 B2 Sheet 5 of 11 x • 150 •B <8> • Q ® • a El Your Health Manager z Z Z y / / 157 / / 155 I Your Health Index Excellent Daily Dose '/. Very Good Z zZ zz% zz zZ z% zzZ % z zz zz z% Z zz zz zZ zz z zz zz zZ 158 Good 1 Fair Poor Z Z z z zz FIG. 5 Activity Level Nutrition Mind Sleep Centering Daily Activity Problem Solver How You Feel 159 X 156a Nutrition 2100 2300 X 156b Activity Level ^ 550 -— 563 X 156c 1 Daily Data Mind Centering o o X Sleep 8hr X 156b Daily Activities 161 ^ 100 156c X How You Feel 5.0 10hr ^ 78 ^ Fair ^ 3.6 / / / / / / / / / / / / / / / / / / / / 1 Body Stats 156a / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / • Case3:15-cv-02579 Document1-2 Filed06/10/15 Page11 of 28 U.S. Patent US 8,073,707 B2 Sheet 6 of 11 Dec. 6,2011 160 L • •H 8 • Oe • 6 r 13 / % Z 7, / / Your Health Manager / / / Y, 7 % V// JNut'ri'tib'n' 7 % y////////////////^Z^^/^//Z^d\ 1250 •«w 0 y f'K'Jis / / 165 / / / / / ^ • / / «<- 0 Z Z 2 1100 ^ 180 v. 7 •«~w Z z % ^ 185 % z W- Q o / • — H W- / 170 a ill ^ 9:30 Siiv / / / / / / / / / v/ 6^00 12:30 190 @ M T W 1 2 9 3 4 10 11 8 T 15 16 17 18 22 23 24 25 29 30 / x/ / / / / s S / 7 12 6 13 14 19 20 21 / / / / 26 27 28 F 5 195 FIG. 6 / / / / / / / —s v/ / / / / / — S Z 175-> / / / / / / / / / / _ /• Case3:15-cv-02579 Document1-2 Filed06/10/15 Page12 of 28 U.S. Patent Dec. 6, 2011 US 8,073,707 B2 Sheet 7 of 11 200 L a • IS 0 • Q ® • 6 HI / / / / / / Z % z Your Health Manager Z Z % % z z z z z z z z z Z z zZ zz zZ 205 zz zz zz zz zz zz zz zz zz zz Z 220 zz z Z Z zZ zz zz y/, A^.y-Lovoi — / / / / 2700 2900 2600 :45 / / / / / CO El • H M L 12 1 2 3 4 5 6 7 8 9 10 11 "H V FIG. 7 / / / / / / / / / / W -M / / / / / / 210 / / / / / / / / / / /Q9 N/ 225 \(i§) y M T W T F s s 1 8 2 9 3 10 4 5 12 6 7 11 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 230 / / / / / / / / / / / / / / / Case3:15-cv-02579 Document1-2 Filed06/10/15 Page13 of 28 U.S. Patent Dec. 6, 2011 US 8,073,707 B2 Sheet 8 of 11 250 Z • •H <8) • Q 0 • 6 —r H Z Z Your Health Manager % % / ^Mind Centering' $Y////////////^^^^ V, % Z Z 35min % 255 7 % o •ap tr 15min 2607 / / o / / / / 265 / GSR 12 1 2 3 4 5 6 7 8 9 10 1112 1 2 3 4 5 6 7 819110 11 12 % % / / / / / / / / / / / / / / 270 % % / / / / / / Low % % z zz zZ zz zz zz zz zz z / / / High % z / / / / / / / / / 280 V: Z Z FIG. 8 M T W T F 1 2 3 4 5 8 9 10 11 12 15 16 17 18 19 22 23 24 25 26 29 30 S S 6 7 14 21 28 13 20 27 / / / / / / / / / / / / 285 / / Case3:15-cv-02579 Document1-2 Filed06/10/15 Page14 of 28 U.S. Patent Dec. 6,2011 US 8,073,707 B2 Sheet 9 of 11 290 L • •a ® • Q ® • 6 51 % z Your Health Manager % Z zz Z ^:4ieVp. zz zz 295 5:55 7hr. 10min. zz 10:45 zz \ 305 V 300 4 Z 210 Z zz TempJl2 1 [2 [3 [4 [5 6 7 819 [10 11 12 112 3 [4 5 [7 jS 9 10 ll i2 zz High zzz zz Z 315 zz zz zz zz Low zz ^wvy^Wvyvvv Motion V^MAMA^NAA/VWyiAy* Z zz zz zz s s zZ 320 M T W T F zz 6 5 7 2 3 4 1 zz 1 13 14 9 10 11 12 8 zz 20 21 15 16 17 18 19 zz 27 28 22 23 24 25 26 zz 30 29 zz 325 \Q Z FIG. 9 / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / tar Case3:15-cv-02579 Document1-2 Filed06/10/15 Page15 of 28 U.S. Patent US 8,073,707 B2 Sheet 10 of 11 Dec. 6, 2011 z • 330 •H • D © • 6 % zz z Z z zz zz Z 335 ^ zz ^ zzz zz zz zz zz zz zz zz zz zz Z 340 Z Z z Z zZ zz zz zz / / / Your Health Manager / % % % % Z H / / / 8 7 9 10 11 12 / / / / / 13 Personal Hygine % / / / / / / / / / / Bathe Brush Teeth/Floss 3 Good Bowels FIG. 10 ssS^^ / / / / / / / / / fci Personal Time Quality Time Work Time Lesure Time Mind Stimulations 3: / / / / / / / / / / / £ £ £ / / b. M 1 T W T F s s 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 / / / / / / / / / / / / / 345 Case3:15-cv-02579 Document1-2 Filed06/10/15 Page16 of 28 U.S. Patent Dec. 6, 2011 Sheet 11 of 11 US 8,073,707 B2 350 L • •B • Q 0 • ft H / % Z zz (^-Realth-lhaex; zz zz zZ 365 210 zz zz Mon zz Sleep Jun 10 zz Nutrition zz z Activity zz Level zz Mind zz Centering * Z 360 Z zz Daily Activity zz zz How You zz Feel zz zZ 355 zz zz Z zz zz zZ z Z zZ z % / / Your Health Manager / / / / / / / / / 76% Tues Wed Thurs Fri Sat Jun11 Jun 12 Jun 13 Jun14 Jun15 i=l_ / / 32% ^ L Sun Jun 16 ^ iiJlia! FIG. 11 / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / M T W T F s s 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 / / / / / / / / / / / / / / / / £* Case3:15-cv-02579 Document1-2 Filed06/10/15 Page17 of 28 US 8,073,707 B2 1 2 SYSTEM FOR DETECTING, MONITORING, AND REPORTING AN INDIVIDUAL'S PHYSIOLOGICAL OR CONTEXTUAL STATUS tus data from at least one of the data indicative of one or more physiological parameters, the derived data, and analytical status data that has previously been generated. The central monitoring unit also includes a data storage device for retrievably storing the data it receives and generates. The disclosed system also includes means for establishing electronic com­ munication between the sensor device and the central monitoring unit. Examples may include various known types of 5 RELATED APPLICATION DATA This patent application is a continuation of U.S. application Ser. No. 09/595,660 filed Jun. 16, 2000, now issued as U.S. Pat. No. 7,689,437 and owned by the assignee of the present application long range 10 FIELD OF THE INVENTION The present invention relates to a system for monitoring health, wellness and fitness, and in particular, to a system for collecting and storing at a remote site data relating to an individual's physiological state, lifestyle, and various contex­ tual parameters, and making such data and analytical infor­ mation based on such data available to the individual, preferably over an electronic network. 15 20 BACKGROUND OF THE INVENTION Research has shown that a large number of the top health problems in society are either caused in whole or in part by an unhealthy lifestyle. More and more, our society requires people to lead fast-paced, achievement-oriented lifestyles that often result in poor eating habits, high stress levels, lack of exercise, poor sleep habits and the inability to find the time to center the mind and relax. Recognizing this fact, people are becoming increasingly interested in establishing a healthier lifestyle. Traditional medicine, embodied in the form of an HMO or similar organizations, does not have the time, the training, or the reimbursement mechanism to address the needs of those individuals interested in a healthier lifestyle. There have been several attempts to meet the needs of these individuals, including a profusion of fitness programs and exercise equip­ ment, dietary plans, self-help books, alternative therapies, and most recently, a plethora of health information web sites on the Internet. Each of these attempts is taigetedto empower the individual to take charge and get healthy. Each of these attempts, however, addresses only part of the needs of indi­ viduals seeking a healthier lifestyle and ignores many of the real barriers that most individuals face when trying to adopt a healthier lifestyle. These barriers include the fact that the individual is often left to himself or herself to find motivation, to implement a plan for achieving a healthier lifestyle, to monitor progress, and to brainstorm solutions when problems arise; the fact that existing programs are directed to only certain aspects of a healthier lifestyle, and rarely come as a complete package; and the fact that recommendations are often not targeted to the unique characteristics of the indi­ vidual or his life circumstances. 25 30 35 40 45 50 55 SUMMARY OF THE INVENTION A system is disclosed for detecting, monitoring and report­ ing human physiological information. The system includes a sensor device which generates at least one of data indicative of one or more physiological parameters and derived data from at least a portion of the data indicative of one or more physiological parameters when placed in proximity with at least a portion of the human body. The system also includes a central monitoring unit located remote from the sensor device. The central monitoring unit generates analytical sta- 60 65 wireless transmission devices, or a physical or a wireless coupling to a computer which in turn establishes electronic communication with the central monitoring unit over an electronic network such as the Internet. Also included in the system is a means for transmitting the data indicative of one or more physiological parameters, the derived data, and/or the analytical status data to a recipient, such as the individual or a third party authorized by the individual. Also disclosed is a method of detecting, monitoring and reporting human physiological information. The method includes generating at least one of data indicative of one or more physiological parameters of an individual and derived data from at least a portion of the data indicative of one or more physiological parameters using a sensor device adapted to be placed in proximity with at least a portion of the human body. The at least one of the data indicative of one or more physiological parameters and the derived data are transmitted to a central monitoring unit remote from said sensor device and retrievably stored in a storage device. Analytical status data is generated from at least a portion of at least one of the data indicative of one or more physiological parameters, the derived data and the analytical status data, and at least one of the data indicative of one or more physiological parameters, the derived data and the analytical status data is transmitted to a recipient. The sensor device includes one or more sensors for gener­ ating signals in response to physiological characteristics of the individual. The sensor device may also include a proces­ sor that is adapted to generate the data indicative of one or more physiological parameters from the signals generated by theoneormoresensors.Theprocessormayalsobeadaptedto generate the derived data. Alternatively, the derived data may be generated by the central monitoring unit. The central monitoring unit may be adapted to generate one or more web pages containing the data indicative of one ormore physiological parameters, the derived data, and/orthe analytical status data. The web pages generated by the central monitoring unit are accessible by the recipient over an elec­ tronic network, such as the Internet. Alternatively, the data indicative of one or more physiological parameters, the derived data, and/or the analytical status data may be transmitted to the recipient in a physical form such as mail or facsimile. The system and method may also obtain life activities data of the individual and may use such life activities data when generating the analytical status data. Furthermore, the sensor device may also be adapted to generate data indicative of one or more contextual parameters of the individual. The system and method may then use the data indicative of one or more contextual parameters when generating the analytical status data, Also disclosed is a system for monitoring the degree to which an individual has followed a suggested routine. The system includes a sensor device adapted to generate at least one of data indicative of one or more physiological parameters of the individual and derived data from at least a portion of the data indicative of one or more physiological parameters when the sensor device is placed in proximity with at least a short range Case3:15-cv-02579 Document1-2 Filed06/10/15 Page18 of 28 US 8,073,707 B2 3 portion of the human body. Also included is a means for transmitting the data that is generated by the sensor device to a central monitoring unit remote from the sensor device and means for providing life activities data of the individual to the central monitoring unit. The central monitoring unit is adapted to generate and provide feedback to a recipient relat­ ing to the degree to which the individual has followed the suggested routine. The feedback is generated from at least a portion of at least one of the data indicative of one or more physiological parameters, the derived data, and the life activi­ ties data. Also disclosed is a method of monitoring the degree to 4 FIG. 7 is a representation of a preferred embodiment of the activity level web page according to an aspect of the present invention; 5 invention; 10 which an individual has followed a suggested routine. The method includes receiving, at a central monitoring unit, at 15 parameters of said individual and derived data based on at least a portion of the data indicative of one or more physi­ more physiological parameters and the derived data are gen­ 20 erated by a sensor device when placed in proximity with at least a portion of the human body. Also received at the central monitoring unit is life activities data of the individual. The method further includes generating at the central monitoring 25 unit feedback relating to the degree to which the individual has followed the suggested routine, the feedback being gen­ erated from at least a portion of at least one of the data indicative of one or more physiological parameters of the 30 individual, the derived data, and the life activities data, and providing the feedback to a recipient. The suggested routine may include a plurality of categories, wherein the feedback is generated and provided with ^ respect to each of the categories. Examples of the categories include nutrition, activity level, mind centering, sleep, and daily activities. The feedback may be provided in graphical form and may be contained in one or more web pages gener­ ated by the central monitoring unit. Alternatively, the feed- 40 back may be transmitted to the recipient in a physical form. BRIEF DESCRIPTION OF THE DRAWINGS Further features and advantages of the present invention will be apparent upon consideration of the following detailed FIG. 9 is a representation of a preferred embodiment of the sleep web page according to an aspect of the present inven­ tion; FIG. 10 is a representation of a preferred embodiment of the daily activities web page according to an aspect of the present invention; and FIG. 11 is a representation of a preferred embodiment of the Health Index web page according to an aspect of the present invention. least one of data indicative of one or more physiological ological parameters, wherein the data indicative of one or FIG. 8 is a representation of a preferred embodiment of the mind centering web page according to an aspect of thepresent 45 DESCRIPTION OF THE PREFERRED EMBODIMENTS In general, according to the present invention, data relating to the physiological state, the lifestyle and certain contextual parameters of an individual is collected and transmitted, either subsequently or in real-time, to a site, preferably remote from the individual, where it is stored for later manipulation and presentation to a recipient, preferably over an electronic network such as the Internet. Contextual param­ eters as used herein means parameters relating to the environ­ ment, surroundings and location of the individual, including, but not limited to, air quality, sound quality, ambient tempera­ ture, global positioning and the like. Referring to FIG. 1, located at user location 5 is sensor device 10 adapted to be placed in proximity with at least a portion of the human body. Sensor device 10 is preferably worn by an individual user on his or her body, for example as part of a garment such as a form fitting shirt, or as part of an arm band or the like. Sensor device 10, includes one or more sensors, which are adapted to generate signals in response to physiological characteristics of an individual, and a microprocessor. Proximity as used herein means that the sensors of sensor device 10 are sepa­ rated from the individual's body by a material or the like, or a distance such that the capabilities of the sensors are not impeded. Sensor device 10 generates data indicative of various physiological parameters of an individual, such as the indi­ the following drawings, in which like reference characters vidual's heart rate, pulse rate, beat-to-beat heart variability, 50 EKG or ECG, respiration rate, skin temperature, core body refer to like parts, and in which: temperature, heat flow off the body, galvanic skin response or FIG. 1 is a diagram of an embodiment of a system for GSR, EMG, EEG, EOG, blood pressure, body fat, hydration monitoring physiological data and lifestyle over an electronic level, activity level, oxygen consumption, glucose or blood network according to the present invention; sugar level, body position, pressure on muscles or bones, and FIG. 2 is a block diagram of an embodiment of the sensor 55 UV radiation absorption. In certain cases, the data indicative device shown in FIG. 1; of thevarious physiological parameters is the signal or signals FIG. 3 is a block diagram of an embodiment of the central themselves generated by the one or more sensors and in certain other cases the data is calculated by the microproces­ monitoring unit shown in FIG. 1; sor based on thesignal or signals generated by theone or more FIG. 4 is a block diagram of an alternate embodiment of the 60 sensors. Methods for generating data indicative of various central monitoring unit shown in FIG. 1; physiological parameters and sensors to be used therefor are FIG. 5 is a representation of a preferred embodiment of the well known. Table 1 provides several examples of such well Health Manager web page according to an aspect of the known methods and shows the parameter in question, the present invention; method used, the sensor device used, and the signal that is FIG. 6 is a representation of a preferred embodiment of the 65 generated. Table 1 also provides an indication as to whether nutrition web page according to an aspect of the present further processing based on the generated signal is required to invention; generate the data. description of the present invention, taken in conjunction with Case3:15-cv-02579 Document1-2 Filed06/10/15 Page19 of 28 US 8,073,707 B2 6 5 TABLE 1 Parameter Method Sensor Signal Further Processing Heart Rate Pulse Rate EKG BVP DC Voltage Change in Resistance Yes Yes Beat-to-Beat Variability EKG Heart Rate 2 Electrodes LED Emitter and Optical Sensor 2 Electrodes DC Voltage Yes Skin Surface Potentials Chest Volume Change Surface Temperature Probe Esophageal or Rectal Probe Heat Flux Skin Conductance 3-10 Electrodes DC Voltage No Strain Gauge Change in Resistance Yes Thermistors Change in Resistance Yes Thermistors Change in Resistance Yes Thermopile 2 Electrodes DC Voltage Change in Resistance Yes No Skin Surface Potentials Skin Surface Potentials Eye Movement 3 Electrodes DC Voltage No Multiple Electrodes DC Voltage Yes DC Voltage Yes Non-Invasive Korotkuff Sounds Body Impedance Body Movement Thin Film Piezoelectric Sensors Electronic Sphygromarometer 2 Active Electrodes Accelerometer Change in Resistance Yes Change in Impedance DC Voltage, Capacitance Changes Yes Yes Oxygen Uptake Electro-chemical DC Voltage Change Yes Non-Invasive N/A Electro-chemical Mercury Switch Array DC Voltage Change DC Voltage Change Yes Yes N/A Thin Film Piezoelectric Sensors UV Sensitive Photo Cells DC Voltage Change Yes DC Voltage Change Yes Respiration Rate Skin Temperature Core Temperature Heat Flow Galvanic Skin Response EMG EEG EOG Blood Pressure Body Fat Activity in Interpreted G Shocks per Minute Oxygen Consumption Glucose Level Body Position (e.g. supine, erect, sitting) Muscle Pressure UV Radiation Absorption N/A The types of data listed in Table 1 are intended to be examples of the types of data that can be generated by sensor device 10. It is to be understood that other types of data relating to other parameters can be generated by sensor device 10 without departing from the scope of the present invention. The microprocessor of sensor device 10 may be pro­ grammed to summarize and analyze the data. For example, the microprocessor can be programmed to calculate an aver­ age, minimum or maximum heart rate or respiration rate over 40 45 a defined period of time, such as ten minutes. Sensor device 10 may be able to derive information relating to an individu­ al's physiological state based on the data indicative of one or more physiological parameters. The microprocessor of sen­ sor device 10 is programmed to derive such information using known methods based on the data indicative of one or more physiological parameters. Table 2 provides examples of the type of information that can be derived, and indicates some of the types of data that can be used therefor. TABLE 2 Derived Information Data Used Ovulation Sleep onset/wake Skin temperature, core temperature, oxygen consumption Beat-to-beat variability, heart rate, pulse rate, respiration rate, skin temperature, core temperature, heat flow, galvanic skin response, EMG, EEG, EOG, blood pressure, oxygen consumption Heart rate, pulse rate, respiration rate, heat flow, activity, oxygen consumption Heart rate, pulse rate, respiration rate, heat flow, activity, oxygen consumption Skin temperature, core temperature Heart rate, pulse rate, respiration rate, heat flow, activity, oxygen consumption EKG, beat-to-beat variability, heart rate, pulse rate, respiration rate, skin temperature, heat flow, galvanic skin response, EMG, EEG, blood pressure, activity, oxygen consumption Calories burned Basal metabolic rate Basal temperature Activity level Stress level Case3:15-cv-02579 Document1-2 Filed06/10/15 Page20 of 28 US 8,073,707 B2 8 7 TABLE 2-continued Derived Information Data Used Relaxation level EKG, beat-to-beat variability, heart rate, pulse rate, respiration rate, skin temperature, heat flow, galvanic skin response, EMG, EEG, blood pressure, activity, oxygen consumption EKG, heart rate, pulse rate, respiration rate, heat flow, blood pressure, activity, oxygen consumption Heart rate, pulse rate, heat flow, oxygen consumption Maximum oxygen consumption rate Rise time or the time it takes to rise from a resting rate to 85% of a target maximum Time in zone or the time heart rate was above 85% of a target maximum Recovery time or the time it takes heart rate to return to a resting rate after heart rate was above 85% of a target maximum Heart rate, pulse rate, heat flow, oxygen consumption Heart rate, pulse rate, heat flow, oxygen consumption Additionally, sensor device 10 may also generate data indicative of various contextual parameters relating to the environment surrounding the individual. For example, sensor device 10 can generate data indicative of the air quality, sound level/quality, light quality or ambient temperature near the individual, or even the global positioning of the individual. Sensor device 10 may include one or more sensors for gen­ erating signals in response to contextual characteristics relating to the environment surrounding the individual, the signals ultimately being used to generate the type of data described above. Such sensors are well known, as are methods for generating contextual parametric data such as air quality, sound level/quality, ambient temperature and global positioning. FIG. 2 is a block diagram of an embodiment of sensor device 10. Sensor device 10 includes at least one sensor 12 and microprocessor 20. Depending upon the nature of the signal generated by sensor 12, the signal can be sent through one or more of amplifier 14, conditioning circuit 16, and analog-to-digital converter 18, before being sent to micropro­ cessor 20. For example, where sensor 12 generates an analog signal in need of amplification and filtering, that signal can be sent to amplifier 14, and then on to conditioning circuit 16, which may, for example, be a band pass filter. The amplified and conditioned analog signal can then be transferred to ana­ log-to-digital converter 18, where it is converted to a digital signal. The digital signal is then sent to microprocessor 20. Alternatively, if sensor 12 generates a digital signal, that signal can be sent directly to microprocessor 20. A digital signal or signals representing certain physiologi­ cal and/or contextual characteristics of the individual user may be used by microprocessor 20 to calculate or generate data indicative of physiological and/or contextual parameters of the individual user. Microprocessor 20 is programmed to derive information relating to at least one aspect of the indi­ vidual's physiological state. It should be understood that microprocessor 20 may also comprise other forms of proces­ sors or processing devices, such as a microcontroller, or any other device that can be programmedto perform the function­ ality described herein. The data indicative of physiological and/or contextual parameters can, according to one embodiment of the present invention, be sent to memory 22, suchas flash memory, where it is storeduntil uploaded in the manner to be described below. Although memory 22 is shown in FIG. 2 as a discrete element, it will be appreciated that it may also be part of microproces­ sor 20. Sensor device 10 also includes input/output circuitry 24, which is adapted to output and receive as input certain data signals in the manners to be described herein. Thus, memory 22 of the sensor device 10 will build up, over time, a 20 25 30 35 40 45 50 55 60 65 store of data relating to the individual user's body and/or environment. That data is periodically uploaded from sensor device 10 and sent to remote central monitoring unit 30, as shown in FIG. 1, where it is stored in a database for subse­ quent processing and presentation to the user, preferably through a local or global electronic network such as the Inter­ net. This uploading of data can be an automatic process that is initiated by sensor device 10 periodically or upon the happen­ ing of an event such as the detection by sensor device 10 of a heart rate below a certain level, or can be initiated by the individual user or some third party authorized by the user, preferably according to some periodic schedule, such as every day at 10:00 p.m. Alternatively, rather than storing data in memory 22, sensor device 10 may continuously upload data in real time. The uploading of data from sensor device 10 to central monitoring unit 30 for storage canbe accomplished in various ways. In one embodiment, the data collected by sensor device 10 is uploaded by first transferring the data to personal com­ puter 35 shown in FIG. 1 by means of physical connection 40, which, for example, may be a serial connection such as an RS232 or USB port. This physical connection may also be accomplished by using a cradle, not shown, that is electronically coupled to personal computer 35 into which sensor device 10 can be inserted, as is common with many commer­ cially available personal digital assistants. The uploading of data could be initiated by then pressing a button on the cradle or could be initiated automatically upon insertion of sensor device 10. The data collected by sensor device 10 may be uploaded by first transferring the data to personal computer 35 by means of short-range wireless transmission, such as infrared or radio transmission, as indicated at 45. Once the data is received by personal computer 35, it is optionally compressed and encrypted by any one of a variety of well knownmethods andthen sent out over a local or global electronic network, preferably the Internet, to central moni­ toring unit 30. It should be noted that personal computer 35 can be replaced by any computing device that has access to and that can transmit and receive data through the electronic network, such as, for example, a personal digital assistant such as the Palm VII sold by Palm, Inc., or the Blackberry 2-way pager sold by Research in Motion, Inc. Alternatively, the data collected by sensor device 10, after being encrypted and, optionally, compressedby microproces­ sor 20, may be transferred to wireless device 50, such as a 2-way pager or cellular phone, for subsequent long distance wireless transmission to local telco site 55 using a wireless protocol such as e-mail or as ASCII or binary data. Local telco site 55 includes tower 60 that receives the wireless transmis­ sion from wireless device 50 and computer 65 connected to Case3:15-cv-02579 Document1-2 Filed06/10/15 Page21 of 28 US 8,073,707 B2 9 10 tower 60. According to the preferred embodiment, computer 65 has access to the relevant electronic network, such as the Internet, and is used to transmit the data received in the form of the wireless transmission to the central monitoring unit 30 over the Internet. Although wireless device 50 is shown in FIG. 1 as a discrete device coupled to sensor device 10, it or a device having the same or similar functionality may be embedded as part of sensor device 10. Sensor device 10 may be provided with a button to be used to time stamp events such as time to bed, wake time, and time of meals. These time stamps are stored in sensor device 10 and are uploaded to central monitoring unit 30 withthe rest of the data as described above. The time stamps may include a digitally recorded voice message that, after being uploaded to central monitoring unit 30, are translated using voice recognition technology into text or some other information format that can be used by central monitoring unit 30. In addition to using sensor device 10 to automatically collect physiological data relating to an individual user, a kiosk could be adapted to collect such data by, for example, weighing the individual, providing a sensing device similar to sensor device10 onwhich an individual places his orher hand or another part of his or her body, or by scanning the indi­ vidual's body using, for example, laser technology or an iStat blood analyzer. The kiosk would be provided with processing capability as described herein and access to the relevant electronic network, and would thus be adapted to send the collected data to the central monitoring unit 30 through the electronic network.A desktop sensing device, again similar to sensor device 10, on which an individual places his or her hand or another part of his or her body may also be provided. For example, such a desktop sensing device could be a blood pressure monitor in which an individual places his or her arm. An individual might also wear a ring having a sensor device 10 incorporated therein. A base, not shown, could then be provided which is adapted to be coupled to the ring. The desktop sensing device or the base just described may then be coupled to a computer such as personal computer 35 by means of a physical or short range wireless connection so that the collected data could be uploaded to central monitoring unit 30 over the relative electronic network in the manner described above. A mobile device such as, for example, a personal digital assistant, might also be provided with a sensor device 10 incorporated therein. Such a sensor device 10 would be adapted to collect data when mobile device is placed in proximity with the individual's body, such as by holding the device in the palm of one's hand, and upload the collected data to central monitoring unit 30 in any of the ways described herein. Furthermore, in addition to collecting data by automatically sensing such data in the manners described above, indi­ viduals can also manually provide data relating to various life activities that is ultimately transferred to and stored at central monitoring unit 30. An individual user can access a web site maintained by central monitoring unit 30 and can directly input information relating to life activities by entering text freely, by responding to questions posed by the web site, or by clicking through dialog boxes provided by the web site. Cen­ tral monitoring unit 30 can also be adapted to periodically send electronic mail messages containing questions designed to elicit information relating to life activities to personal computer 35 or to some other device that can receive elec­ tronic mail, such as a personal digital assistant, a pager, or a cellular phone. The individual would then provide data relat­ ing to life activities to central monitoring unit 30 by responding to the appropriate electronic mail message with the rel­ evant data. Central monitoring unit 30 may also be adapted to place a telephone call to an individual user in which certain questions would be posed to the individual user. The user could respond to the questions by entering information using a telephone keypad, or by voice, in which case conventional voice recognition technology would be used by central moni­ toring unit 30 to receive and process the response. The tele­ phone call may also be initiated by the user, in which case the user could speak to a person directly or enter information using the keypad or by voice/voice recognition technology. Central monitoring unit 30 may also be given access to a source of information controlled by the user, for example the user's electronic calendar such as that provided with the Outlook product sold by Microsoft Corporation of Redmond, Wash., from which it could automatically collect information. The data relating to life activities may relate to the eating, sleep, exercise, mind centering or relaxation, and/or daily living habits, patterns and/or activities of the individual, Thus, sample questions may include: What did you have for lunch today? What time did you go to sleep last night? What time did you wake up this morning? How long did you run on the treadmill today? Feedback may also be provided to a user directly through sensor device 10 in a visual form, for example through an LED or LCD or by constructing sensor device 10, at least in part, of a thermochromatic plastic, in the form of an acoustic signal or in the form of tactile feedback such as vibration, Such feedback may be a reminder or an alert to eat a meal or take medication or a supplement such as a vitamin, to engage in an activity such as exercise or meditation, or to drink water when a state of dehydration is detected. Additionally, a reminder or alert can be issued in the event that a particular physiological parameter such as ovulation has been detected, a level of calories burned during a workout has been achieved or a high heart rate or respiration rate has been encountered, As will be apparent to those of skill in the art, it may be possible to "download" data from central monitoring unit 30 to sensor device 10. The flow of data in such a download process would be substantially the reverse of that described above with respect to the upload of data from sensor device 10. Thus, it is possible that the firmware of microprocessor 20 of sensor device 10 can be updated or altered remotely, i.e., the microprocessor can be reprogrammed, by downloading new firmware to sensor device 10 from central monitoring unit 30 for such parameters as timing and sample rates of sensor device 10. Also, the reminders/alerts provided by sen­ sor device 10 may be set by the user using the web site maintained by central monitoring unit 30 and subsequently downloaded to the sensor device 10. Referring to FIG. 3, a block diagram of an embodiment of central monitoring unit 30 is shown. Central monitoring unit 30 includes CSU/DSU 70 which is connected to router 75, the main function of which is to take data requests or traffic, both incoming and outgoing, and direct such requests and traffic for processing or viewing on the web site maintained by central monitoring unit 30. Connected to router 75 is firewall 80. The main purpose of firewall 80 is to protect the remainder of central monitoring unit 30 from unauthorized or malicious intrusions. Switch 85, connected to firewall 80, is used to direct data flow between middleware servers 95a through 95c and database server 110. Load balancer 90 is provided to spread the workload of incoming requests among the identi­ cally configured middleware servers 95a through 95c. Load balancer 90, a suitable example of which is the F5 Serverlron product sold by Foundry Networks, Inc. of San Jose, Calif, analyzes the availability of each middleware server 95a through 95c, and the amount of system resources being used 5 lo 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-2 Filed06/10/15 Page22 of 28 US 8,073,707 B2 11 12 in eachmiddleware server 95a through 95c, in order to spread tasks among them appropriately. Central monitoring unit 30 includes network storage device 100, such as a storage area network orSAN, whichacts as the central repository for data. In particular, network storage device 100 comprises a database that stores all data gath­ ered for each individual user in the manners described above. An example of a suitable network storage device 100 is the Symmetrix product sold by EMC Corporation of Hopkinton, Mass. Although only one network storage device 100 is shown in FIG. 3, it will be understood that multiple network storage devices of various capacities couldbe useddepending on the data storage needs of central monitoring unit 30. Cen­ tral monitoring unit 30 also includes database server 110 which is coupled to network storage device 100. Database server 110 is made up of two main components: a large scale multiprocessor server and an enterprise type software server component such as the 8/8i component sold by Oracle Cor­ poration of Redwood City, Calif, or the 506 7 component sold by Microsoft Corporation of Redmond, Wash. The primary functions of database server 110 are that of providing access upon request to the data stored in network storage device 100, and populating network storage device 100 with new data. Coupled to network storage device100 is controller 115, which typically comprises a desktop personal computer, for managing the data stored in network storage device 100. Middleware servers 95a through 95c, a suitable example of which is the 220R Dual Processor soldby SunMicrosystems, Inc. of Palo Alto, Calif, each contain software for generating and maintaining the corporate or home web page or pages of the web site maintained by central monitoring unit 30. As is known inthe art, a web page refers to a block or blocks of data available on the World-Wide Web comprising a file or files written in Hypertext Markup Language or HTML, and a web site commonly refers to any computer on the Internet running a World-Wide Web server process. The corporate or home web page or pages are the opening or landing web page or pages that are accessible by all members of the general public that visit the site by using the appropriate uniform resource locator or URL. As is known in the art, URLs are the form of address used on the World-Wide Web and provide a standard way of specifying the location of an object, typically a web page, on the Internet. Middleware servers 95a through 95c also each contain software for generating and maintaining the web pages of the web site of central monitoring unit 30 that can only be accessed by individuals that register and become members of central monitoring unit 30. The member users will be those individuals who wish to have their data stored at central monitoring unit 30. Access by such member users is controlled using passwords for security purposes. Preferred embodiments of those web pages are described in detail below and are generated using collected data that is stored in the database of network storage device 100. Middleware servers 95a through 95c also contain software for requesting data from and writing data to network storage device 100 through database server 110. When an individual user desires to initiate a session with the central monitoring unit 30 for the purpose of entering data into the database of network storage device 100, viewing his or her data stored in the database of network storage device 100, or both, the user visits the home web page of central monitoring unit 30 using a browser program such as Internet Explorer distributed by Microsoft Corporation of Redmond, Wash., and logs in as a registered user. Load balancer 90 assigns the user to one of the middleware servers 95a through 95c, identified as the chosen middleware server. A user will preferably be assigned to a chosen middleware server for eachentire session. The chosen middleware server authenticates the user using any one of many well known methods, to ensure that only the true user is permitted to access the information in the database. A mem­ ber usermay also grant access to his or her data to a third party such as a health care provider or a personal trainer. Each authorized third party may be given a separate password and may view the member user's data using a conventional browser. It is therefore possible for both the user and the third party to be the recipient of the data. When the user is authenticated, the chosen middleware server requests, through database server 110, the individual user's data from network storage device 100 for a predeter­ mined time period. The predetermined time period is prefer­ ably thirty days. The requested data, once received from network storage device 100, is temporarily stored by the chosen middleware server in cache memory. The cached data is used by the chosen middleware server as the basis for presenting information, in the form of web pages, to the user again through the user's browser. Each middleware server 95a through 95c is provided with appropriate software for generating such web pages, including software for manipu­ lating and performing calculations utilizing the data to put the data in appropriate format for presentation to the user. Once the user ends his or her session, the data is discarded from cache. When the user initiates a new session, the process for obtaining and caching data for that user as described above is repeated. This caching system thus ideally requires that only one call to the network storage device 100 be made per session, thereby reducing the traffic that database server 110 must handle. Should a request from a user during a particular session require data that is outside of a predetermined time period of cached data already retrieved, a separate call to network storage device 100 may be performed by the chosen middleware server. The predetermined time period should be chosen, however, such that such additional calls are minimized. Cached data may also be saved in cache memory so that it can be reused when a user starts a new session, thus eliminating the need to initiate a new call to network storage device 100. As described in connection with Table 2, the microproces­ sor of sensor device 10 may be programmed to derive infor­ mation relating to an individual's physiological state based on the data indicative of one or more physiological parameters. Central monitoring unit 30, and preferably middleware servers 95a through 95c, may also be similarly programmed to derive such information based on the data indicative of one or more physiological parameters. It is also contemplated that a user will input additional data during a session, for example, information relating to the user's eating or sleeping habits. This additional data is preferably stored by the chosen middleware server in a cache during the duration of the user's session. When the user ends the session, this additional new data stored in a cache is transferred by the chosen middleware server to database server 110 for population in network storage device 100. Alternatively, in addition to being stored in a cache for poten­ tial use during a session, the input data may also be immedi­ ately transferred to database server 110 for population in network storage device 100, as part of a write-through cache system which is well known in the art. Data collected by sensor device 10 shown in FIG. 1 is periodically uploaded to central monitoring unit 30. Either by long distance wireless transmission or throughpersonal com­ puter 35, a connection to central monitoring unit 30 is made through an electronic network, preferably the Internet. In particular, connection is made to load balancer 90 through CSU/DSU 70, router 75, firewall 80 and switch 85. Load 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-2 Filed06/10/15 Page23 of 28 US 8,073,707 B2 13 14 balancer 90 then chooses one of the middleware servers 95a user to address as possible barriers to a healthy lifestyle through the problem-solving function of the Health Manager. through 95c to handle the upload of data, hereafter called the The specific information to be surveyed may include: key chosen middleware server. The chosen middleware server individual temperamental characteristics, including activity authenticates the user using any one of many well known methods. If authentication is successful, the data is uploaded 5 level, regularity of eating, sleeping, and bowel habits, initial response to situations, adaptability, persistence, threshold of to the chosen middleware server as described above, and is responsiveness, intensity of reaction, and quality ofmood; the ultimately transferred to database server 110 forpopulation in user's level of independent functioning, i.e., self-organization the network storage device 100. and management, socialization, memory, and academic Referring to FIG. 4, an alternate embodiment of central 10 achievement skills; the user's ability to focus and sustain monitoring unit 30 is shown. In addition to the elements attention, including the user's level of arousal, cognitive shown and described with respect to FIG. 3, the embodiment tempo, ability to filter distractions, vigilance, and self-moni­ of the central monitoring unit 30 shown in FIG. 4 includes a toring; the user's current health status including current mirror network storage device 120 which is a redundant weight, height, and blood pressure, most recent general phybackup of network storage device 100. Coupled to mirror 15 sician visit, gynecological exam, and other applicable physi­ network storage device 120 is controller 122. Data from net­ cian/healthcare contacts, current medications and supple­ work storage device 100 is periodically copied to mirror ments, allergies, and a review of current symptoms and/or network storage device 120 for data redundancy purposes. health-related behaviors; the user's past health history, i.e., Third parties such as insurance companies or research illnesses/surgeries, family history, and social stress events, institutions may be given access, possibly for a fee, to certain 20 such as divorce or loss of a job, that have required adjustment of the information stored in mirror network storage device by the individual; the user's beliefs, values and opinions 120. Preferably, in order to maintain the confidentiality of the about health priorities, their ability to alter their behavior and, individual users who supply data to central monitoring unit what might contribute to stress in their life, and how they 30, these third parties are not given access to such user's manage it; the user's degree of self-awareness, empathy, individual database records, but rather are only given access 25 empowerment, and self-esteem, and the user's current daily routines for eating, sleeping, exercise, relaxation and com­ to the data stored in mirror network storage device 120 in pleting activities of daily living; and the user's perception of aggregate form. Such third parties may be able to access the the temperamental characteristics of two key persons in their information stored in mirror network storage device 120 life, for example, their spouse, a friend, a co-worker, or their through the Internet using a conventional browser program. Requests from third parties may come in through CSU/DSU 30 boss, and whether there are clashes present in their relation70, router 75, firewall 80 and switch 85. In the embodiment ships that might interfere with a healthy lifestyle orcontribute shown in FIG. 4, a separate load balancer 130 is provided for to stress. spreading tasks relating to the accessing and presentation of Each member user will have access, through the home web data from mirror drive array 120 among identically config­ page of central monitoring unit 30, to a series of web pages ured middleware servers 135a through 135c. Middleware 35 customized for that user, referred to as the Health Manager, servers 135a through 135c each contain software for enabling The opening Health Manager web page 150 is shown in FIG. the third parties to, using a browser, formulate queries for 5. The Health Manager web pages are the main workspace information from mirror network storage device 120 through area for the member user. The Health Manager web pages separate database server 125. Middleware servers 135a comprise a utility through which central monitoring unit 30 through 135c also contain software for presenting the infor- 40 provides various types and forms of data, commonly referred to as analytical status data, to the user that is generated from mation obtained from mirror network storage device 120 to the data it collects or generates, namely one or more of: the the third parties over the Internet in the form of web pages. In data indicative of various physiological parameters generated addition, the third parties can choose from a series ofprepared reports that have information packaged along subject matter by sensor device 10; the data derived from the data indicative 45 of various physiological parameters; the data indicative of lines, such as various demographic categories. As will be apparent to one of skill in the art, instead of various contextual parameters generated by sensor device 10; giving these third parties access to the backup data stored in and the data input by the user. Analytical status data is char­ mirror network storage device 120, the third parties may be acterized by the application of certain utilities or algorithms given access to the data stored in network storage device 100. to convert one or more of the data indicative of various physiAlso, instead of providing load balancer 130 and middleware 50 ological parameters generated by sensor device 10, the data servers 135a through 135c, the same functionality, although derived from the data indicative of various physiological at a sacrificed level of performance, could be providedby load parameters, the data indicative of various contextual param­ balancer 90 and middleware servers 95a through 95c. eters generated by sensor device 10, and the data input by the When an individual user first becomes a registered user or user into calculated health, wellness and lifestyle indicators. member, that user completes a detailed survey. The purposes 55 For example, based on data input by the user relating to the of the survey are to: identify unique characteristics/circum­ foods he or she has eaten, things such as calories and amounts stances for each user that they might need to address in order of proteins, fats, carbohydrates, and certain vitamins can be to maximize the likelihood that they will implement and calculated. As another example, skin temperature, heart rate, maintain a healthy lifestyle as suggested by central monitor­ respiration rate, heat flow and/or GSR can be used to provide ing unit 30; gather baseline data which will be used to set 60 an indicator to the user of his or her stress level over a desired initial goals for the individual user and facilitate the calcula­ time period. As still another example, skin temperature, heat tion and display of certain graphical data output such as the flow, beat-to-beat heart variability, heart rate, pulse rate, res­ Health Index pistons; identify unique user characteristics and piration rate, core temperature, galvanic skin response, EMG, circumstances that will help central monitoring unit 30 cus­ EEG, EOG, blood pressure, oxygen consumption, ambient tomize the type of content provided to the user in the Health 65 sound and body movement or motion as detected by a device Manager's Daily Dose; and identify unique user characteris­ such as an accelerometer can be used to provide indicators to tics and circumstances that the Health Manager can guide the the user of his or her sleep patterns over a desired time period. Case3:15-cv-02579 Document1-2 Filed06/10/15 Page24 of 28 US 8,073,707 B2 15 16 Located on the opening Health Manager web page 150 is and 170 which illustrate actual and taiget nutritional facts, Health Index 155. Health Index 155 is a graphical utility used respectively as pie charts, and nutritional intake charts 175 to measure and provide feedback to member users regarding and 180 which show total actual nutritional intake and taiget their performance and the degree to which they have suc­ nutritional intake, respectively as pie charts. Nutritional fact ceeded in reaching a healthy daily routine suggested by cen- 5 charts 165 and 170 preferably show a percentage breakdown tral monitoring unit 30. Health Index 155 thus provides an of items such as carbohydrates, protein and fat, and nutri­ indication for the member user to track his or her progress. tional intake charts 175 and 180 are preferably broken down to show components such as total and target calories, fat, Health Index 155 includes six categories relating to the user's carbohydrates, protein, and vitamins. Web page 160 also health and lifestyle: Nutrition, Activity Level, Mind Center­ ing, Sleep, Daily Activities and How You Feel. The Nutrition 10 includes meal and water consumption tracking 185 with time category relates to what, when and how much a person eats entries, hyperlinks 190 which allow the userto directly access and drinks. The Activity Level category relates to how much nutrition-related news items and articles, suggestions for a person moves around. The Mind Centering category relates refining or improving daily routine with respect to nutrition to the quality and quantity of time a person spends engaging and affiliate advertising elsewhere on the network, and calin some activity that allows the body to achieve a state of 15 endar 195 for choosing between views having variable and profound relaxation while the mind becomes highly alert and selectable time periods. The items shown at 190 may be focused. The Sleep categoryrelates to the quality and quantity selected and customized based on information learned about of a person's sleep. The Daily Activities category relates to the individual in the survey and on their performance as the daily responsibilities and health risks people encounter. measured by the Health Index. Finally, the How You Feel category relates to the general 20 The Activity Level category of Health Index 155 is perception that a person has about how they feel on a particu­ designed to help users monitor how and when they move lar day. Each category has an associated level indicator or around during the day and utilizes both data input by the user piston that indicates, preferably on a scale ranging from poor and data sensed by sensor device 10. The data input by the to excellent, how the user is performing with respect to that user may include details regarding the user's daily activities, 25 for example the fact that the user worked at a desk from 8 a.m. category. When each member user completes the initial survey to 5 p.m. and then took an aerobics class from 6 p.m. to 7 p.m. described above, a profile is generated that provides the user Relevant data sensed by sensor device 10 may include heart with a summary of his or her relevant characteristics and life rate, movement as sensed by a device such as an accelerometer, heat flow, respiration rate, calories burned, GSR and circumstances. A plan and/or set of goals is provided in the form of a suggested healthy daily routine. The suggested 30 hydration level, which may be derived by sensor device 60 or healthy daily routine may include any combination of specific central monitoring unit 30. Calories burned may be calculated suggestions for incorporating propernutrition, exercise, mind in a variety of manners, including: the multiplication of the centering, sleep, and selected activities of daily living in the type of exercise input by the user by the duration of exercise user's life. Prototype schedules may be offered as guides for input by the user; sensed motion multiplied by time of motion how these suggested activities can be incorporated into the 35 multiplied by a filter constant; or sensed heat flux multiplied by time multiplied by a filter constant. user's life. The user may periodically retake the survey, and The Activity Level Health Index piston level is preferably based on the results, the items discussed above will be determined with respect to a suggested healthy daily routine adjusted accordingly. The Nutrition category is calculated from both data input that includes: exercising aerobically for a pre-set time period, by the user and sensed by sensor device 10. The data input by 40 preferably 20 minutes, or engaging in a vigorous lifestyle the user comprises the time and duration of breakfast, lunch, activity for a pre-set time period, preferably one hour, and dinner and any snacks, and the foods eaten, the supplements burning at least a minimum target number of calories, pref­ such as vitamins that are taken, and the water and other liquids erably 205 calories, through the aerobic exercise and/or lif­ consumed during a relevant, pre-selected time period. Based estyle activity. The minimum target number of calories may upon this data and on stored data relating to known properties 45 be set according to information about the user, such as sex, age, height and/or weight. Parameters utilized in the calcula­ of various foods, central monitoring unit 30 calculates well tion of the relevant piston level include the amount of time known nutritional food values such as calories and amounts of proteins, fats, carbohydrates, vitamins, etc., consumed. spent exercising aerobically or engaging in a vigorous lif­ The Nutrition Health Index piston level is preferably deter­ estyle activity as input by the user and/or sensed by sensor mined with respect to the following suggested healthy daily 50 device 10, and the number of calories burned above preroutine: eat at least three meals; eat a varied diet consisting of calculated energy expenditure parameters. 6-11 servings of bread, pasta, cereal, and rice, 2-4 servings Information regarding the individual user's movement is fruit, 3-5 servings of vegetables, 2-3 servings of fish, meat, presented to the user through activity level web page 200 poultry, dry beans, eggs, and nuts, and 2-3 servings of milk, shown in FIG. 7, which may include activity graph 205 in the yogurt and cheese; and drink 8 or more 8 ounce glasses of 55 form of a bar graph, for monitoring the individual user's water. This routine may be adjusted based on information activities in one of three categories: high, medium and low about the user, such as sex, age, height and/or weight. Certain intensity with respect to a pre-selected unit of time. Activity nutritional targets may also be set by the user or for the user, percentage chart 210, in the form or a pie chart, may also be relating to daily calories, protein, fiber, fat, carbohydrates, provided for showing the percentage of a pre-selected time and/or water consumption and percentages of total consump- 60 period, such as one day, that the user spent in each category, tion. Parameters utilized in the calculation of the relevant Activity level web page 200 may also include calorie section piston level include the number of meals per day, the number 215 for displaying items such as total calories burned, daily of glasses of water, and the types and amounts of food eaten target calories burned, total caloric intake, and duration of each day as input by the user. aerobic activity. Finally, activity level web page 200 may Nutritional information is presented to the user through 65 include at least one hyperlink 220 to allow a user to directly nutrition web page 160 as shown in FIG. 6. The preferred access relevant news items and articles, suggestions for refin­ nutritional web page 160 includes nutritional fact charts 165 ing or improving daily routine with respect to activity level Case3:15-cv-02579 Document1-2 Filed06/10/15 Page25 of 28 US 8,073,707 B2 17 18 and affiliate advertising elsewhere on the network. Activity the times the user went to sleep and woke up and a rating of level web page 200 may be viewed in a variety of formats, and the quality of sleep. As noted in Table 2, the data from sensor may include user-selectable graphs and charts such as a bar device 10 that is relevant includes skin temperature, heat flow, graph, pie chart, or both, as selectable by Activity level check beat-to-beat heart variability, heart rate, pulse rate, respiration boxes 225. Activity level calendar 230 is provided for select- 5 rate, core temperature, galvanic skin response, EMG, EEG, ing among views having variable and selectable time periods. EOG, blood pressure, and oxygen consumption. Also rel­ evant is ambient sound and body movement or motion as The items shown at 220 may be selected and customized detected by a device such as an accelerometer. This data can based on information learned about the individual in the then be used to calculate or derive sleep onset and wake time, survey and on their performance as measured by the Health 10 sleep interruptions, and the quality and depth of sleep. Index. The Mind Centering category of Health Index 155 is The Sleep Health Index piston level is determined with designed to help users monitorthe parameters relating to time respect to a healthy daily routine including getting a mini­ spent engaging in certain activities which allow the body to mum amount, preferably eight hours, of sleep each night and achieve a state of profound relaxation while the mind having a predictable bed time and wake time. The specific becomes focused, and is based upon both data input by the 15 parameters which determine the piston level calculation user and data sensed by the sensor device 10. In particular, a include the number of hours of sleep per night and the bed user may input the beginning and end times of relaxation time and wake time as sensed by sensor device 10 or as input activities such as yoga or meditation. The quality of those by the user, and the quality of the sleep as rated by the user or activities as determined by the depth of a mind centering derived from other data. event can be measured by monitoring parameters including 20 Information regarding sleep is presented to the user through sleep web page 290 shown in FIG. 9. Sleep web page skin temperature, heart rate, respiration rate, and heat flow as 290 includes a sleep duration indicator 295, based on either sensed by sensor device 10. Percent change in GSR as derived data from sensor device 10 or on data input by the user, either by sensor device 10 or central monitoring unit 30 may together with user sleep time indicator 300 and wake time also be utilized. The Mind Centering Health Index piston level is preferably 25 indicator 305. A quality of sleep rating 310 input by the user calculated with respect to a suggested healthy daily routine may also be utilized and displayed. If more than a one day that includes participating each day in an activity that allows time interval is being displayed on sleep web page 290, then the body to achieve profound relaxation while the mind stays sleep duration indicator 295 is calculated and displayed as a highly focused for at least fifteen minutes. Parameters utilized cumulative value, and sleep time indicator 300, wake time in the calculation of the relevant piston level include the 30 indicator 305 and quality of sleep rating 310 are calculated amount of time spent in a mind centering activity, and the and illustrated as averages. Sleep web page 290 also includes percent change in skin temperature, heart rate, respiration a user-selectable sleep graph 315 which calculates and dis­ rate, heat flow or GSR as sensed by sensor device 10 com­ plays one sleep related parameter over a pre-selected time pared to a baseline which is an indication of the depth or interval. For illustrative purposes, FIG. 9 shows heat flow quality of the mind centering activity. 35 over a one-day period, which tends to be lower during sleep­ Information regarding the time spent on self-reflection and ing hours and higher during waking hours. From this infor­ relaxation is presented to the user through mind centering mation, a person's bio-rhythms can be derived. Sleep graph web page 250 shown in FIG. 8. For each mind centering 315 may also include a graphical representation of data from activity, referred to as a session, the preferred mind centering an accelerometer incorporated in sensor device 10 which web page 250 includes the time spent during the session, 40 monitors the movement of the body. The sleep web page 290 may also include hyperlinks 320 which allow the user to shown at 255, the target time, shown at 260, comparison directly access sleep related news items and articles, sugges­ section 265 showing target and actual depth of mind center­ tions for refining or improving daily routine with respect to ing, or focus, and a histogram 270 that shows the overall level of stress derived from such things as skin temperature, heart sleep and affiliate advertising available elsewhere on the netrate, respiration rate, heat flow and/or GSR. In comparison 45 work, and a sleep calendar 325 for choosing a relevant time interval. The items shown at 320 may be selected and cus­ section 265, the human figure outline showing target focus is tomized based on information learned about the individual in solid, and the human figure outline showing actual focus the survey and on their performance as measured by the ranges from fuzzy to solid depending on the level of focus. The preferred mind centering web page may also include an Health Index. indication of the total time spent on mind centering activities, 50 The Activities of Daily Living category of Health Index shown at 275, hyperlinks 280 which allow the user to directly 155 is designed to help users monitor certain health and safety access relevant news items and articles, suggestions for refin­ related activities and risks and is based entirely on data input ing or improving daily routine withrespect to mind centering by the user. The Activities of Daily Living category is divided and affiliate advertising, and a calendar 285 for choosing into four sub-categories: personal hygiene, which allows the among views having variable and selectable time periods. 55 user to monitor activities such as brushing and flossing his or The items shown at 280 may be selected and customized her teeth and showering; health maintenance, that tracks based on information learned about the individual in the whether the user is taking prescribed medication or supple­ survey and on their performance as measured by the Health ments and allows the user to monitor tobacco and alcohol Index. consumption and automobile safety such as seat belt use; The Sleep category of Health Index 155 is designed to help 60 personal time, that allows the user to monitor time spent users monitor their sleep patterns and the quality of their socially with family and friends, leisure, and mind centering sleep. It is intended to help users learn about the importance activities; andresponsibilities, that allows the user to monitor of sleep in their healthy lifestyle and the relationship of sleep certain work and financial activities such as paying bills and to circadian rhythms, being the normal daily variations in household chores. body functions. The Sleep category is based upon both data 65 The Activities of Daily Living Health Index piston level is input by the user and data sensed by sensor device 10. The preferably determined with respect to the healthy daily rou­ tine described below. With respect to personal hygiene, the data input by the user for each relevant time interval includes Case3:15-cv-02579 Document1-2 Filed06/10/15 Page26 of 28 US 8,073,707 B2 19 20 routine requires that the users shower or bathe eachday, brush and floss teeth each day, and maintain regular bowel habits. With respect to health maintenance, the routine requires that the user take medications and vitamins and/or supplements, use a seat belt, refrain from smoking, drink moderately, and monitor health each day with the Health Manager. With respect to personal time, the routine requires the users to spend at least one hour of quality time each day with family and/or friends, restrict work time to a maximumof nine hours a day, spend some time on a leisure or play activity each day, and engage in a mind stimulating activity. With respect to responsibilities, the routine requires the users to do household chores, pay bills, be on time for work, and keep appointments. The piston level is calculatedbased on the degree to which the user completes a list of daily activities as determined by information input by the user. Information relating to these activities is presented to the user through daily activities web page 330 shown in FIG. 10. In preferred daily activities web page 330, activities chart 335, selectable for one or more of the sub-categories, shows whether the user has done what is required by the daily routine. A colored or shaded box indicates that the user has done the required activity, and an empty, non-colored or shaded box indicates that the user has not done the activity. Activities chart 335 can be created and viewed in selectable time intervals. For illustrative purposes, FIG. 10 shows the personal hygiene and personal time sub-categories for a par­ ticular week. In addition, daily activities web page 330 may include daily activity hyperlinks 340 which allow the user to directly access relevant news items and articles, suggestions for improving or refining daily routine with respect to activi­ ties of daily living and affiliate advertising, and a daily activi­ ties calendar 345 for selecting a relevant time interval. The items shown at 340 may be selected and customized based on information learned about the individual in the survey and on their performance as measured by the Health Index. The How You Feel category of Health Index 155 is designed to allow users to monitor their perception of how they felt on a particular day, and is based on information, essentially a subjective rating, that is input directly by the user. A user provides a rating, preferably on a scale of 1 to 5, with respect to the following nine subject areas: mental sharp­ ness; emotional and psychological well being; energy level; ability to cope with life stresses; appearance; physical well being; self-control; motivation; and comfort in relating to others. Those ratings are averaged and used to calculate the relevant piston level. Referring to FIG. 11, Health Index web page 350 is shown. Health Index web page 350 enables users to view the perfor­ mance of their Health Index over a user selectable time interval including any number of consecutive or non-consecutive days. Using Health Index selector buttons 360, the user can select to view the Health Index piston levels for one category, or can view a side-by-side comparison of the Health Index piston levels for two or more categories. For example, a user might want to just turn on Sleep to see if their overall sleep rating improved over the previous month, much in the same way they view the performance of their favorite stock. Alter­ natively, Sleep and Activity Level might be simultaneously displayed in order to compare and evaluate Sleep ratings with corresponding Activity Level ratings to determine if any dayto-day correlations exist. Nutrition ratings might be displayed with How You Feel for a pre-selected time interval to deter­ mine if any correlation exists between daily eating habits and how they felt during that interval. For illustrative purposes, FIG. 11 illustrates a comparison of Sleep and Activity Level piston levels for the week of June 10 through June 16. Health Index web page 350 also includes tracking calculator 365 that displays access information and statistics such as the total number of days the user has logged in and used the Health Manager, the percentage of days the user has used the Health Manager since becoming a subscriber, and percentage of time the user has used the sensor device 10 to gather data. Referring again to FIG. 5, opening Health Manager web page 150 may include a plurality of user selectable category summaries 156a through 156/J one corresponding to each of the Health Index 155 categories. Each category summary 156a through 156/presents a pre-selected filtered subset of the data associated with the corresponding category. Nutri­ tion category summary 156a displays daily target and actual caloric intake. Activity Level category summary 1566 dis­ plays daily taiget and actual calories burned. Mind Centering category summary 156c displays target and actual depth of mind centering or focus. Sleep category summary 156d dis­ plays target sleep, actual sleep, and a sleep quality rating. Daily Activities category summary 156e displays a target and actual score based onthe percentage of suggested daily activi­ ties that are completed. The How You Feel category summary 156/shows a target and actual rating for the day. Opening Health Manager web page 150 also may include Daily Dose section 157 which provides, on a daily time interval basis, information to the user, including, but not limited to, hyperlinks to news items and articles, commentary and reminders to the user based on tendencies, such as poor nutri­ tional habits, determined from the initial survey. The com­ mentary for Daily Dose 157 may, for example, be a factual statement that drinking 8 glasses of water a day can reduce the risk of colon cancer by as much as 32%, accompanied by a suggestion to keep a cup of water by your computer or on your desk at work and refill often. Opening Health Manager web page 150 also may include a Problem Solver section 158 that actively evaluates the user's performance in each of the cat­ egories of Health Index 155 and presents suggestions for improvement. For example, if the system detects that a user's Sleep levels have been low, which suggest that the user has been having trouble sleeping, Problem Solver 158 can pro­ vide suggestions for way to improve sleep. Problem Solver 158 also may include the capability of user questions regard­ ing improvements in performance. Opening Health Manager web page 150 may also include a Daily Data section 159 that launches an input dialog box. The input dialog box facilitates input by the user of the various data required by the Health Manager. As is known in the art, data entry may be in the form of selection from pre-defined lists or general free form text input. Finally, opening Health Manager web page 150 may include Body Stats section 161 which may provide informa­ tion regarding the user's height, weight, body measurements, body mass index or BMI, and vital signs such as heart rate, blood pressure or any of the identified physiological parameters. The terms and expressions which have been employed herein are used as terms of description and not as limitation, and there is no intention in the use of such terms and expres­ sions of excluding equivalents of the features shown and described or portions thereof, it being recognized that various modifications are possible within the scope of the invention claimed. Although particular embodiments of the present invention have been illustrated in the foregoing detailed description, it is to be further understood that the present invention is not to be limited to just the embodiments disclosed, but that they are capable of numerous rearrangements, modifications and substitutions. 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-2 Filed06/10/15 Page27 of 28 US 8,073,707 B2 21 22 What is claimed is: 1. A system for detecting, monitoring, and reporting a status of an individual to a user, the system comprising: a first sensor adapted to generate data indicative of a first physiological parameter of the individual if said first sensor is in proximity to the individual; a second sensor adapted to generate data indicative of a second physiological parameter of the individual if said second sensor is in proximity to the individual; a processing unit in electronic communication with said first sensor and said second sensor; a central monitoring unit in electronic communication with at least one of said sensors and said processing unit; and an output device in electronic communication with at least one of said processing unit and said central monitoring unit, wherein at least one of said processing unit and said central monitoring unit is programmed (a) to generate at least one of a derived physiological status parameter of the individual and a derived parameter related to an activity in which the individual has engaged said derived parameters based on both of said data indicative of said first physiological parameter of the individual and said data indicative of said second physi­ ological parameter of the individual, and (b) to cause said output device to present to a user indica­ tors of at least one of said derived parameters of the individual in relation to indicators of at least one of (i) said data indicative of said first physiological parameter of the individual, and (ii) said data indicative of said second physiological parameter of the individual. 2. The system of claim 1 wherein at least one of said first sensor, said second sensor, and said processing unit is in a unitary wearable device. 3. The system of claim 1 wherein the system further comprises an input device to enable a user to enter data into the system. 4. The system of claim 3 wherein at least one of said processing unit and said central monitoring unit is pro­ grammed to cause said output device to present to a user said indicators of at least one of said derivedparameters in relation to said indicators of at least one of data entered by a user and another derived parameter of the individual, said another derived parameter of the individual being at least one of a derived physiological parameter of the individual and a derived parameter related to an activity in which the indi­ vidual has engaged. 5. The system of claim1 further comprising an input device for providing life activities data of the individual to the sys­ tem. 6. The system of claim 5 wherein at least one of said processing unit and said central monitoring unit is pro­ grammed to cause said output device to present to a user said indicators of at least one of said derivedparameters in relation to said indicators of at least one of said life activities data of the individual and another derived parameter of the indi­ vidual, said another derived parameter of the individual being at least one of a derived physiological parameter of the indi­ vidual and a derived parameter related to an activity in which the individual has engaged. 7. The system of claim 1 wherein at least one of said derived parameters is energy expenditure. 8. The system of claim 1 wherein said data generated by the system is aggregated into a database accessible to a user. 9. The system of claim 3 wherein said data generated by the system and said data entered by the user is aggregated into a database accessible to a user. 10. The system of claim 5 wherein said data generated by the system and said life activities data is aggregated into a database accessible to a user. 5 11. The system of any one of claim 1,8,9, or 10 whereinthe individual. user is at least one of an authorized user ^ the 12. The system of any one of claims 8-10 wherein said database is stored on a network storage device. 10 13. The system of any one of claims 8-10 wherein at least one of said processing unit and said central monitoring unit is programmed to receive a query from a user, to access said database, and to cause said output device to generate a report based on said query with said data from said database. 14. The system of claim 1 wherein at least one of said 15 processing unit and said central monitoring unit is pro­ grammed to generate feedback data relating to a degree to which the individual has achieved one or more preset goals, said feedback data being generated from at least a portion of at least one of said data indicative of said first physiological 20 parameter of the individual, said data indicative of said sec­ ond physiological parameter of the individual, and at least one of said derived parameters, wherein at least one of said processing unit and said central monitoring unit is pro­ grammed to cause said output device to provide said feedback 25 data to a user. 15. The system of claim 14 wherein said one or more preset goals comprise a target caloric burn for the individual or a target caloric intake of the individual. 30 16. The system of claim 1 wherein said output device is at least one of a personal computer, a personal digital assistant, a pager, and a mobile phone. 17. The system of claim 1 wherein said indicators pre­ sented to a user by the output device are visual for at least one 35 0f (a) at ieast one 0f said derived parameters of the individual, (b) said data indicative of said first physiological parameter of the individual, and (c) said data indicative of said second physiological parameter of the individual. 40 45 50 18. The system of claim 1 wherein said indicators pre­ sented to a user by the output device are in audio form for at least one of (a) at least one of said derived parameters of the individual, (b) said data indicative of said first physiological parameter of the individual, and (c) said data indicative of said second physiological parameter of the individual. 19. The system of claim 1 wherein said indicators pre­ sented to a user by the output device are tactile for at least one of (a) at least one of said derived parameters of the individual, (b) said data indicative of said first physiological parameter of the individual, and (c) said data indicative of said second physiological parameter of the individual. 20. The system of claim 1 wherein said central monitoring unit is adapted to generate one or more web pages comprising said data generated by the system, and wherein said output 55 device makes one or more of said web pages accessible to a user over the Internet. 21. The system of claim 1 wherein the system is fee based. 60 65 22. The system of claim 1 wherein at least one of said indicators represents at least one of life activities, activities of daily living, data entered by the user, an activity level of the individual, stress of the individual, mind centering of the individual, sleep of the individual, energy expenditure of the individual, or how the individual feels. 23. The system of claim 1 wherein at least one of said indicators are compared to a baseline parameter of the indi­ vidual. Case3:15-cv-02579 Document1-2 Filed06/10/15 Page28 of 28 US 8,073,707 B2 23 24 24. The system of claim 1 wherein at least one of said central monitoring unit and said processing unit is pro­ grammed to provide suggestions, said suggestions being based on said relation of said indicators of at least one of said derived parameters of the individual to said indicators of at least one of said data indicative of said first physiological parameter of the individual and said data indicative of said second physiological parameter of the individual. Document1-3 Filed06/10/15 Pagel of 64 Exhibit Case3:15-cv-02579 Document1-3 Filed06/10/15 Page2 of 64 US008398546B2 (12) United States Patent (io) Patent No.: US 8,398,546 B2 (45) Date of Patent: Mar. 19, 2013 Pacione et al. (54) (75) SYSTEM FOR MONITORING AND MANAGING BODY WEIGHT AND OTHER PHYSIOLOGICAL CONDITIONS INCLUDING ITERATIVE AND PERSONALIZED PLANNING, INTERVENTION AND REPORTING CAPABILITY (73) Assignee: BodyMedia, Inc., Pittsburgh, PA (US) (*) Notice: (22) Filed: (65) U.S. CI (2006.01) 600/300; 600/301; 128/920; 128/921; 705/2; 705/3; 706/45 Field of Classiflcation Search 600/300-301, 600/509, 500, 529, 356, 485, 549; 128/920-925; 434/262, 127, 326, 107, 219, 238, 247; 705/2-3 See application file for complete search history. References Cited U.S. PATENT DOCUMENTS 3/1975 James et al. 6/1977 Raggiotti et al. (Continued) FOREIGN PATENT DOCUMENTS BR P0001075-8 11/2001 (Continued) OTHER PUBLICATIONS Thermal Gap Fillers, Kent Young, Feb. 6, 2001 (article downloaded from www.chomerics.com). (Continued) Primary Examiner — Sam Yao Assistant Examiner — Marie Archer (74) Attorney, Agent, or Firm —GTC Law Group LLP & Affiliates; John A. Monocello, III ABSTRACT k. nutrition and activity management system is disclosed that monitors energy expenditure of an individual through the use of a body-mounted sensing apparatus. The apparatus is par­ ticularly adapted for continuous wear. The system is also adaptable or applicable to measuring a number of other physi­ ological parameters and reporting the same and derivations of such parameters. A weight management embodiment is directed to achieving an optimum or preselected energy bal­ ance between calories consumed and energy expended by the user. An adaptable computerized nutritional tracking system is utilized to obtain data regarding food consumed, Relevant and predictive feedback is provided to the user regarding the mutual effect of the user's energy expenditure, food con­ sumption and other measured or derived or manually input physiological contextual parameters upon progress toward said goal. Prior Publication Data May 26, 2005 Related U.S. Application Data (63) Continuation-in-part of application No. 10/638,588, filed on Aug. 11, 2003, now Pat. No. 6,605,038, which is a continuation of application No. 09/602,537, filed on Jun. 23, 2000, now Pat. No. 7,689,437, which is a continuation-in-part of application No. 09/595,660, filed on Jun. 16, 2000. (60) Provisional application No. 60/502,764, filed on Sep. 13, 2003, provisional application No. 60/555,280, filed on Mar. 22, 2004. 505^ 610-— 615-- i — BUFFER FLASH A/D r-450 1 H 2 AXIS ACCEL AMP/OFFSET -495 _ rSU 15 hri 520 1 I AMP 1 r-.__ 465 1 GSR SENSORS FILTER/CONDITIONING^ I 1 £460 KB^KTMTI-I "cSiSn" H I r6D5 ^-595 H iv~500 p BUFFER ' VOLTAGE REGULATOR OSCILLATOR ~ 29 Claims, 27 Drawing Sheets — BUFFER SRAM BATTERY (52) 3,870,034 A 4,031,365 A Sep. 13, 2004 US 2005/0113650 Al Int. CI. A61B 5/00 (56) Subject to any disclaimer, the term of this patent is extended or adjusted under 35 U.S.C. 154(b) by 32 days. Appl.No.: 10/940,214 (51) (58) Inventors: Christopher Pacione, Pittsburgh. PA (US); Steve Menke, Mars, PA (US); David Andre, Pittsburgh. PA (US); Eric Teller, Pittsburgh. PA (US); Scott Safler, Pittsburgh, PA (US); Raymond Pelletier, Pittsbuigh, PA (US); Mark Handel, Pittsburgh, PA (US); Jonathan Farringdon, Pittsburgh. PA (US); Eric Hsiung, Pittsburgh, PA (US); Suresh Vishnubhatla, Wexford, PA (US); James Hanlon, Library, PA (US); John M. Stivoric, Pittsburgh, PA (US); Neal Spruce, Westlake Village, CA (US); Steve Shassberger, Lansing, MI (US) (21) I BATTERY MONITOR PROCESSING UNIT —545 3 AXIS ACCEL 1—550 rfreceiver dg 490 DRIVER RESET CIRCUIT"! DRIVER SWITCH —J——r-590 LEDS [-—475 "M>85 (((«< , ~U 560 VIBRATOR l/'580 ^600 LED LATCH/ DRIVER HANT RF TRANSCEIVER f- 1 RINGER 1—455 1 —575 WIRELESS DEVICE ^558 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page3 of 64 US 8,398,546 B2 Page 2 U.S. PATENT DOCUMENTS 4,052,979 4,129,125 4,148,304 4,151,831 4,192,000 4,312,358 4,364,398 4,377,171 4,407,295 4,488,558 4,509,531 4,531,527 4,539,994 4,557,273 4,608,987 4,622,979 4,627,738 4,672,977 4,676,254 4,757,453 RE32,758 4,784,162 4,803,625 4.819.860 4,827,943 4,828,257 4,883,063 4,891,756 4,917,108 4,951,197 4,958,645 4.966.154 4,981,139 5,007,427 5,012,411 5,027,824 5.038.792 5,040,541 5,050,612 5,072,458 5,111,818 5,135,311 5,148,002 5.178.155 5,179,958 5,216,599 5,224,479 5.263.491 5,285,398 5,305,244 5,335,664 5.353.793 5,410,471 5,435,315 5,445,149 5,458,123 5.469.861 5,474,090 5,476,103 5,484,389 5,491,651 5,511,553 5,515,858 5,515,865 5,523,730 5,524,618 5,555,490 5,559,497 5,564,429 5,566,679 5,581,238 5.581.492 5,583,758 5,611,085 5,617,477 5,622,180 5,645,068 5,652,570 10/1977 Scherr et al. 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European Search Report, EP11159897, search mailed Aug. 2, 2011, 4 pages. * cited by examiner Case3:15-cv-02579 Document1-3 Filed06/10/15 Page6 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 1 of 27 60 LOCAL TELCO 55 r TELCO COMPUTER 50 rx 65 WIRELESS DEVICE 30 10 1' SENSOR DEVICE 40 z CENTRAL r—^ MONITORING UNIT / "-x THE INTERNET 45 35 _i ^5 USER LOCATION FIG. 1 L r n14 AMPLIFIER zdi SENSOR CONDITIONING CIRCUIT 16 FIG. 2 A/D r* CONVERTER ~f ^18 zz2g AUDIO PLAYER 21 MICROPROCESSOR -10 I/O I /:24 MEMORY /l22 J n K> W ON 4^ 'VI s* 00 so s* 00 e C/2 <1 K> o K> 2- ST 5/3 K> o sp ss p C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page7 of 64 CSU/DSU 70 FIG. 3 ROUTER FIREWALL 80 NETWORK STORAGE 110 100 /I DATABASE SERVER SWITCH r 85 LOAD BALANCER 90 115 MIDDLEWARE SERVER Zl 95c /—95b MIDDLEWARE SERVER MIDDLEWARE SERVER 95a C/2 K> W ON 4^ 'VI 00 00 d <1 K> o re re cr 5/3 K> o sP ss P n C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page8 of 64 FIG. 4 CSU/DSU 70 ROUTER NETWORK STORAGE DATABASE SERVER 100 110 FIREWALL 80 130 ^1353 MIDDLEWARE SERVER SWITCH 85 LOAD BALANCER 115 1 H35b MIDDLEWARE SERVER MIRROR NETWORK STORAGE DATABASE SERVER 120 125 90 LOAD BALANCER MIDDLEWARE SERVER 122 95c MIDDLEWARE SERVER /-95b MIDDLEWARE SERVER MIDDLEWARE SERVER 95a C/2 K> W 0\ 4^ 'VI s* 00 so 00 s* d <1 K> o ST re re 5/3 K> o sp ss n p C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page9 of 64 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page10 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 5 of 27 150 3mm [o] INTERNET EXPLORER File Edit View Go Favorites Help ^ Back =» Forward 0 Copy ® Refresh Address http:// lS Home ® Search Favorites M Print Links Font EI .htm Your Health Manager 1577 155 L Your Health Index Excellent Dally Dose Very Good Good 158^ Fair Problem Solver Poor Wnc Activity Level Centering ZL156a Nutrition Sleep H156b Activity Level = 2100 550 = 2300 563 156d Sleep 8 hr. Daiy How You Activities Feel a156c Mind Centering © 161^ a156f How You Feel 100 5.0 78 3.6 ^10 hr. = Fair Daily Data O 156e Daily Activities 159^ FIG. 5 Body Stats : Case3:15-cv-02579 Document1-3 Filed06/10/15 Page11 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 6 of 27 160 L [e] INTERNET EXPLORER •©s file Edit View Go Favorites Help <= Back ® Forward Copy ® Refresh 0 Q E- Home Search Favorites Print M Font Links B .htm Address http:// Your Health Manager yy/ Nutrition : 1250 175i 165 m H • 1100 180i ID 170 m • 185^^^^ 12:30 ® 6:00 8 W T F S 2 3 4 5 6 8 9 10 11 1 2 13 15 16 17 18 19 20 22 23 24 25 26 27 29 30 M T 1 M90 T:195 FIG. 6 S 7 14 21 28 SUCCESS/ ERROR BODY/ PARAMETERS 1010 REMINDER AND TIMEZONE I TRY AGAIN S N. z ARMBAND ERROR i CONFIGURE \RESULT/ CONFIGURE ARMBAND NO DRIVER/ERROR SUCCESS 1020 SUCCESS WEIGHT GOAL 1025 i START OVER PROCESS 1030 'r 1000 VERIFY. APPLY SUCCESS/ ERROR FIG. 7 DIET AND EXERCISE PLAN 1035 START OVER VERIFY. SUCCESS/ APPLY ERROR SELECT X)NE SUCCESS UPDATE ARMBAND UPDATE ARMBAND ERROR 1015-"' I 1^1015 ERROR I VERIFY. VERIFY. SUCCESS VERIFY. APPLY WEIGHT PROGRAM 1005 I USER SELECTS MY PROFILE cr re SZ2 W ON 'VI 4^ so 00 00 d K> o fD 5/3 o K> sP ss n p C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page12 of 64 FIG. 8 1075 WEIGHT ENTRY \YES NUMBER % 6 = 0 / 1065 CURRENT WEIGHT YES <= TARGET WEIGHT NO 7 ASK USER TO VERIFY ENTERED WEIGHT 1055 YES 1060 1050 1045 1080 CALCULATE PREDICTED WEIGHT LOSS FROM NUTRITION AND EE VALUES WEIGHTLOSS RATE I = 0 I SAVE WEIGHT YES /ABS (% CHANGE)' —> 3% SINCE LAST \ WEIGHT , NO ENTER WEIGHT Z ABS (PREDICTED ENTERED LOSS) > =4 NO > = 10 ABS (PREDICTED ENTERED LOSS) CONGRATULATIONS AND RESET WEIGHT GOALS PAGE 1070 1085b YES YES L ERROR PAGE INFORMING USER OF DISCREPANCY AND POSSIBLE REASONS ERROR PAGE AS KING USER TO CONTACT CUSTOMER SUPPORT DUE TO WEIGHT DISCREPANCY 1085a 1040 SZ2 W ON 'VI 4^ 00 s* 00 s* d <1 K> 00 o cr re re 5/3 K> o sP n SS p C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page13 of 64 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page14 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 9 of 27 a1090 1095a L CHOOSE EE METHOD 1095c L CAN'T UPLOAD — (EE METHODV- FROM N RIGHT NOW ' ARMBAND FORGOT TO WEAR ARMBAND CHOOSE UPLOAD METHOD RETREIVE ARMBAND DATA 1095b 1105 'r ESTIMATE EE 7 1100 ESTIMATE EE \ YES , / OFF BODY ^ TIMES h NO 1100 1110 MISSING \ YES MEALS ^ NO RECENT WEIGHT > NO YES AUTOMATIC FIRMWARE -* CHECK > YES ARMBAND UPLOAD ? NO •- FIG. 9 z MANUAL ACTIVITY ENRY BALANCE PAGE NUTRITION LOGGING SYSTEM ENTER WEIGHT REMINDER PAGE 1115 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page15 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 10 of 27 200 •mix] [e] INTERNET EXPLORER file Edit View Go Favorites Help <= Back => ® Forward ® Copy Refresh Q> S- Search Favorites M Font _ Print Links Z & .htm Address http:// I fS Home 13 Your Health Manager & : Activity Level:: :0: •:m m 1 = 2700 = 2900 215 M 12 •:m 1 = :45 2600 2 3 4 5 6 7 8 9 10 11 S-S _ _ • 205^ m •:m -M H M L :0. 210 Wi :0: M :iii $:i :iS :0: 220 225i T W T F S S 6 7 8 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 1 1$ 2 9 3 4 5 ^—230 FIG. 10 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page16 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 11 of 27 250 amm [e] INTERNET EXPLORER File Edit View Go Favorites Help <= => Back Forward ® ® Copy Refresh Address http:// Home Search Favorites M Print Links fg: Font 13 .htm Your Health Manager ii; Mind Centering ^ 255 as min r 260 265 o A. 1R min GSR 12 2 3 4 5 6 7 8 9 2 3 12 5 6 7 8 9 10 High 270s Low 280 M T W T F S 1 2 3 4 5 6 7 8 9 1 0 11 12 13 14 15 16 17 18 19 22 23 24 25 26 29 30 FIG. 11 S 20 21 27 28 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page17 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 12 of 27 290 rjimixi [e] INTERNET EXPLORER File Edit View Go Favorites Help Forward ® Copy Address http:// it 8 i # i i i i i i i ti .• 3i5-< ® Refresh ^ Home S- Search Favorites M _ Print Links /% Font B .htm Your Health Manager i:i: Sleep 295{ 310{ 7hr 10 min 305 300 10:45 5:55 Temp 12 2 3 4 5 6 7 8 9 10 11 12 112 3 4 5 6 7 8 9 10 11 12 High M i i i i i i i 320 i i I i Low Motion M 1 T W T F S 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 22 23 24 25 26 29 30 325 FIG. 12 S 20 21 27 28 JV Case3:15-cv-02579 Document1-3 Filed06/10/15 Page18 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 13 of 27 330 [e] INTERNET EXPLORER File Edit View Go Favorites Help Back Forward Copy Refresh Address http:// Home a- ij M Print Font Links fg: Search Favorites E] .htm Your Health Manager :§l§:^baiiy ActivitiesW§iiiMil§ii§lli: 335 < Personal Time Quality Time Work Time Leisure Time Mind Stimulating M 340 -s T W T F S 12 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 29 30 T~345 FIG. 13 S 28 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page19 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 14 of 27 350 misiixi [o] INTERNET EXPLORER File Edit View Go Favorites Help 4= => ® ® Back Forward Copy Refresh Home Q, a- Search Favorites Print M Links /% Font 13 .htm Address http:// Your Health Manager Health Index > 365 Sleep Nutrition 360 s 210 76% = 32% Mon Tues Wed Thurs Fri Sat Sun Jun 10 Jun 11 Jun 12 Jun 13 Jun 14 Jun 15 Jun 16 1 1 III iil I £%» iiiliifiilili You s iililililiiil Activity Level Mind Centering 7- 355 M T W T F S S 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 1 FIG. 14 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page20 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 15 of 27 1120 1121 1122a 1122b t f Balance] f 1122c 1122cl I i Reports ) ( Profile ) [Update 1122e i ) f Metal Plans j f 1123 1136 ^ Calories f Ph Burned Today Calories Consumed Today Calorie ^ Balance Today I Weight 1 t Messages ) Expert Healteh Tips or Feedback Calendar Dashboard Today 1122f 1125 Goal Actual 2900 1844 - 2400 = 587 1137 burned ^2-Q 0 -0.5 Lbs/Week 1146 you are sedentary for the rest of the day, you will be 177 calories shy of your goal -750 500 1257 -1500 Burned Burned consumed 2250 ^ Goal 2250 -1500 YoiJ have + 1.0 +0.2 TOTAL WEIGHT GAIN Lbs/Week TODAY 210BEGIN WEIGHT 1813 calories left in your daily budget. 205- 200195G0AL WEIGHT 190 185- FIG. 15 GOAL ETA 1135 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page21 of 64 U.S. Patent Mar. 19, 2013 1160 balance = black getMessageKey 1 >40 1150 yes Note for today? no 1155 1160 C1155 *- balance = even getEnergyBalanceQ else <-40 getEnergyBalanceQ balance = red C EE o fD 5/3 ST K> o S &S n S3 P C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page22 of 64 getState getCaloriclntake Message >0 <0 >50 <-50 return-1 ^ r else 1215 FIG. 18 *- predictedCI-goalCI i L return 1 balance = below 1f =0 ^205 goalCI-predictedCI i k balance = above return 0 1210 Returns string "caloricintake.getKeyQ.ee.exer" *• balance = even K> W ON 'VI 4^ so 00 s* C/2 00 d <1 K> o 00 fD ft ST 5/3 K> O Vo S p ss p C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page23 of 64 ' f 1 1 0 getState(EE) 1215 ir 1 1 ' H 1215 ' r 1 1215 FIG. 19 0 getState(EE) 0 getState(CI) setState 1 i' i' 1 YES 'r i' NO BURNING MORE CALORIES THAN CONSUMING? 0 getState(EE) 1215 K> W ON 'VI 4^ s* 00 C/2 00 d <1 K> o fD ft ST C/5 K> O S P ss p C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page24 of 64 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page25 of 64 U.S. Patent US 8,398,546 B2 Sheet 20 of 27 Mar. 19, 2013 400 470 V- 405 410 410 420 420 418 418 0 OQ QQ FIG. 20 475 485 405 400 410 466 438a M) i 430 410 466 o 465 460 o 465 // 418 FIG. 21 o 440 A 418 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page26 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 21 of 27 400 410 405 420 425 418 FIG. 22 400 475 405 418 418 f 420 485 425 410 420 425 FIG. 23 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page27 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 22 of 27 470 400 405 418 410 475 FIG. 24 485 418 400 470 f''' \ 427 428 !• "4® iwast fT 405 A\ 475 V20 vo vs '\\ A\ 430 429 '/ 427 '/ i 430 495 416 410 429 8 $ $ P5 « 426 FIG. 25 427 428 415 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page28 of 64 U.S. Patent Mar. 19, 2013 US 8,398,546 B2 Sheet 23 of 27 410 475 451 / 435 470 455 450 '!/ 610 O 439 585 © 445 615 595 490 437 © 438b V® © FIG. 26 436 440 481a i 420 410 I RECHARGING i 1 RF 1 L _qiRCUJT_ J [TRANSCEJVERj-^- 433 405 400 FIG. 27 480 RECHARGING CIRCUIT TO WALL OUTLET J L TO SERIAL PORT 481b K> W ON 4^ 'VI 00 so 00 d in <1 K> o K> re re ST 5/3 K> o sp ss p C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page29 of 64 FLASH 615 ^600 RESET CIRCUIT ^-595 OSCILLATOR VOLTAGE REGULATOR r605 BAHERY /-450 SRAM 610 A/D LEDS LED LATCH/ DRIVER SWITCH 475 590 490 PROCESSING UNIT 505 500 500 585 DRIVER DRIVER /-580 T 570 FIG. 28 RINGER VIBRATOR 525 — 575 455 465 558 WIRELESS DEVICE HEAT FLUX SENSOR ^-460 GSR SENSORS (((«<• AMP 510 ANT ^ s f i n 555 565 RF RECEIVER RF TRANSCEIVER 550 545 3 AXIS ACCEL BATTERY MONITOR AMP ij"540 AMP 495 £-535 ^30 BUFFER —["FILTER — 515 520 2 AXIS ACCEL FILTER/CONDITIONING AMP/OFFSET BUFFER BUFFER 4^ W ON 'VI 00 oo C/2 d K> 'vi o K> re re ST 5/3 K> O P s ss n P C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page30 of 64 1610 W! 1615 Ai.W! ALG 1 CHANNELS DERIVED FROM SENSOR DATA AND DEMOGRAPHIC INFORMATION / 1600 ^ 7 ' 1 A2,W2 FIG. 29 POST PROCESSOR 1610 ALG 2 1' W2 CONTEXT DETECTOR 1605 *• WN 1620 1610 ALGORITHM OUTPUT AI.WN ALG N K> W ON 4^ 'VI OO C/2 00 d <1 K> o K> ON fD ft ST C/5 K> O S P ss n P C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page31 of 64 Wi Ai.W! ALG 1 1615 7 1610 LAVE, TSAD, HFVar, VSAD, HF, GSR, BMR AND DEMOGRAPHIC INFORMATION 1600 FIG. 30 POST PROCESSOR CONTEXT DETECTOR 1605 A2,W2 ALG2 W2 1620 ENERGY EXPENDITURE 1610 K> W ON 4^ 'VI s* so OO OO C/2 d <1 K> o fD ft ST 5/3 K> O S P ss n p C/5 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page32 of 64 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page33 of 64 US 8,398,546 B2 1 2 SYSTEM FOR MONITORING AND MANAGING BODY WEIGHT AND OTHER PHYSIOLOGICAL CONDITIONS INCLUDING ITERATIVE AND PERSONALIZED PLANNING, INTERVENTION AND REPORTING CAPABILITY With respect to weight loss, specifically, many medical and other commercial methodologies have been developed to assist individuals in losing excess body weight and maintain­ ing an appropriate weight level through various diet, exercise and behavioral modification techniques. Weight Watchers is an example of a weight loss behavior modification system in which an individual manages weight loss with a points system utilizing commercially available foods. All food items are assigned a certain number of points based on serving size and content of fat, fiber and calories. Foods that are high in fat are assigned a higher number of points. Foods that are high in fiber receive a lower number of points. Flealthier foods are typically assigned a lower number of points, so the user is encouraged to eat these food items. A user is assigned a daily points range which represents the total amount of food the user should consume within each day. Instead of directing the user away from a list of forbidden foods, a user is encouraged to enjoy all foods in moderation, as long as they fit within a user's points budget. The program is based on calorie reduction, portion control and modifica­ tion of current eating habits. Exercise activities are also assigned points which are subtracted from the points accu­ mulated by a user's daily caloric intake. Weight Watchers attempts to make a user create a balance of exercise and healthy eating in their life. However, because only caloric value of food is specifically tracked, the program tends to fail in teaching the user about the nutritional changes they need to make to maintain weight loss. Calorie content is not the only measurement that a user should take into control when determining what food items to consume. Items that contain the same caloric content may not be nutritiously similar. So, instead of developing healthy eating habits, a user might become dependent on counting points. It is important to note that the Weight Watchers program deals essentially with caloric intake only and not caloric expenditure, Similarly, Jenny Craig is also a weight loss program. Typi­ cally, an individual is assigned a personal consultant who monitors weight loss progress. In addition, the individual will receive pre-selected menus which are based on the Food Guide Pyramid for balanced nutrition. The menus contain Jenny Craig branded food items which are shipped to the individual's home or any other location chosen by the indi­ vidual. The Jenny Craig program teaches portion control because the food items to be consumed are pre-portioned and supplied by Jenny Craig. However, such a close dietary super­ vision can be a problem once the diet ends because the diet plan does not teach new eating habits or the value of exercise. Instead it focuses mainly on short term weight loss goals. The integration of computer and diet tracking systems has created several new and more automated approaches to weight loss. Available methodologies can be tailored to meet the individual's specific physiological characteristics and weight loss goals. BalanceLog, developed by HealtheTech, Inc. and the subject of U.S. Published Application No. 20020133378 is a software program that provides a system for daily tracking and monitoring of caloric intake and expenditure. The user customizes the program based on metabolism in addition to weight and nutrition goals. The user is able to create both exercise and nutrition plans in addition to tracking progress, However, the BalanceLog system has several limitations. First, a user must know their resting metabolic rate, which is the number of calories burned at rest. The user can measure their resting metabolic rate. However, a more accurate rate can be measured by appointment at a metabolism measurement location. A typical individual, especially an individual who is beginning a weight and nutrition management plan 5 CROSS REFERENCE TO RELATED APPLICATIONS 10 This application is a continuation in part of U.S. applica­ tion Ser. No. 10/638,588, filed Aug. 11, 2003, now U.S. Pat. No. 6,605,038 which is a continuation of U.S. application Ser. No. 09/602,537, filed Jun. 23, 2000, now U.S. Pat. No. 7,689, 437 which is a continuation-in-part of U.S. application Ser. No. 09/595,660, filed Jun. 16, 2000. This application also claims the benefit of U.S. Provisional Application No. 60/502,764 filed on Sep. 13,2003 and U.S. Provisional Appli­ cation No. 50/555,280 filed on Mar. 22, 2004. 15 20 FIELD OF THE INVENTION The present invention relates to a weight control system. More specifically, the system may be used as part of a behav­ ioral modification program for calorie control, weight control 25 or general fitness. In particular, the invention, according to one aspect, relates to an apparatus used in conjunction with a software platform for monitoring caloric consumption and/or caloric expenditure of an individual. Additionally, the inven­ tion relates to a method of tracking progress toward weight 30 goals. BACKGROUND OF THE INVENTION Research has shown that a large number of the top health problems in society are either caused in whole or in part by an unhealthy lifestyle. More and more, our society requires people to lead fast-paced, achievement-oriented lifestyles that often result in poor eating habits, high stress levels, lack of exercise, poor sleep habits and the inability to find the time to center the mind and relax. Additionally, obesity and body weight have become epidemic problems facing a large seg­ ment of the population, notably including children and ado­ lescents. Recognizing this fact, people are becoming increas­ ingly interested in establishing a healthier lifestyle. Traditional medicine, embodied in the form of an HMO or similar oiganization, does not have the time, the training, or the reimbursement mechanism to address the needs of those individuals interested in a healthier lifestyle. There have been several attempts to meet the needs of these individuals, including a perfusion of fitness programs and exercise equip­ ment, dietary plans, self-help books, alternative therapies, and most recently, a plethora of health information web sites on the Internet. Each of these attempts is taigetedto empower the individual to take charge and get healthy. Each of these attempts, however, addresses only part of the needs of indi­ viduals seeking a healthier lifestyle and ignores many of the real barriers that most individuals face when trying to adopt a healthier lifestyle. These barriers include the fact that the individual is often left to himself or herself to find motivation, to implement a plan for achieving a healthier lifestyle, to monitor progress, and to brainstorm solutions when problems arise; the fact that existing programs are directed to only certain aspects of a healthier lifestyle, and rarely come as a complete package; and the fact that recommendations are often not targeted to the unique characteristics of the indi­ vidual or his life circumstances. 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page34 of 64 US 8,398,546 B2 3 may view this requirement as an inconvenience. The system can provide an estimated resting metabolic rate based on a broad population average if a more accurate measurement cannot be made. However, the resting metabolic rate can vary widely between individuals having similar physiological characteristics. Thus, an estimation may not be accurate and would affect future projections of an individual's progress. Second, the system is limited by the interactivity and compliance of the user. Every aspect of the BalanceLog system is manual. Every item a user eats and every exercise a user does must be logged in the system. If a user fails to do this, the reported progress will not be accurate. This manual data entry required by BalanceLog assumes that the user will be in close proximity to a data entry device, such as a personal digital assistant or a personal computer, to enter daily activities and consumed meals. However, a user may not consistently or reliably be near their data entry device shortly thereafter engaging in an exercise or eating activity. They may be performing the exercise activity at a fitness center or otherwise away from such a device. Similarly, a user may not be eating a certain meal at home, so they may not be able to log the information immediately after consuming the meal. Therefore, a user must maintain a record of all food consumed and activities performed so that these items can be entered into the BalanceLog system at a later time. Also, the BalanceLog system does not provide for the possibility of estimation. A user must select the food consumed and the corresponding portion size of the food item. If a time lapse has occurred between the meal and the time of entry and the user does not remember the meal, the data may not be entered accurately and the system would suffer from a lack of accuracy. Similarly, if a user does not remember the details of an exercise activity, the data may not be correct. Finally, the BalanceLog system calculates eneigy expenditure based only upon the information entered by the user. A user may only log an exercise activity such as running on a treadmill for thirty minutes for a particular day. This logging process does not take into account the actual energy expenditure of the individual, but instead relies on averages or look-up tables based upon general population data, which may not be particularly accurate for any specific individual. The program also ignores the daily activities of the user such as walking up stairs or running to catch the bus. These daily activities need to be taken into account for a user to accurately determine their total amount of eneigy expenditure. Similarly FitDay, a software product developed by Cyser Software, is another system that allows a user to track both nutrition and exercise activity to plan weight loss and monitor progress. The FitDay software aids a user in controlling diet through the input of food items consumed. This software also tracks the exercise activity and caloric expenditure through the manual data entry by the user. The FitDay software also enables the user to track and graph body measurements for additional motivation to engage in exercise activity. Also, FitDay also focuses on another aspect of weight loss. The system prompts a user for information regarding daily emo­ tions for analysis of the triggers that may affect a user's weight loss progress. FitDay suffers from the same limitations of Balance Log. FitDay is dependent upon user input for its calculations and weight loss progress analysis. As a result, the information may suffer from a lack of accuracy or compliance because the user might not enter a meal or an activity. Also, the analysis of energy expenditure is dependent on the input of the user and does not take the daily activities of the user into consideration. 4 Overall, if an individual consumes fewer calories than the number of calories burned, they user should experience a net weight loss. While the methods described above offer a plurality of ways to count consumed calories, they do not offer an 5 efficient way to determine the caloric expenditure. Additionally, they are highly dependent upon compliance with rigorous data entry requirements. Therefore, what is lacking in the art is a management system that can accurately and automatically monitor daily activity and eneigy expenditure of the 10 user to reduce the need for strict compliance with and the repetitive nature of manual data entry of information, SUMMARY OF THE INVENTION 15 20 25 30 35 40 45 50 55 60 65 A nutrition and activity management system is disclosed that can help an individual meet weight loss goals and achieve an optimum energy balance of calories burned versus calories consumed. The system may be automated and is also adaptable or applicable to measuring a number of other physiological parameters and reporting the same and derivations of such parameters. The preferred embodiment, a weight management system, is directed to achieving an optimum energy balance, which is essential to progressing toward weight lossspecific goals. Most programs, such as the programs discussed above, offer methods of calorie and food consumption tracking, but that is only half of the equation. Without an accurate estimation of energy expenditure, the optimum energy balance cannot be reached. In other embodiments, the system may provide additional or substitute information regarding limits on physical activity, such as for a pregnant or rehabilitating user, or physiological data, such as blood sugar level, for a diabetic. The management system that is disclosed provides a more accurate estimation of the total energy expenditure of the user, The other programs discussed above can only track energy expenditure through manual input of the user regarding specific physical activity of a certain duration. The management system utilizes an apparatus on the body that continuously monitors the heat given off by a user's body in addition to motion, skin temperature and conductivity. Because the apparatus is continuously worn, data is collected during any physical activity performed by the user, including exercise activity and daily life activity. The apparatus is further designed for comfort and convenience so that long term wear is not unreasonable within a wearer's lifestyle activities. It is to be spe­ cifically noted that the apparatus is designed for both continuous and long term wear. Continuous is intended to mean, however, nearly continuous, as the device may be removed for brief periods for hygienic purposes or other de minimus non-use. Long term wear is considered to be for a substantial portion of each day of wear, typically extending beyond a single day. The data collected by the apparatus is uploaded to the software platform for determining the number of calories burned, the number of steps taken and the duration of physical activity, The management system that is disclosed also provides an easier process for the entry and tracking of caloric consump­ tion. The tracking of caloric consumption provided by the management system is based on the recognition that current manual nutrition tracking methods are too time consuming and difficult to use, which ultimately leads to a low level of compliance, inaccuracy in data collection and a higher per­ centage of false caloric intake estimates. Most users are too busy to log everything they eat for each meal and tend to forget how much they ate. Therefore, in addition to manual input of consumed food items, the user may select one of several other methods of caloric input which may include an Case3:15-cv-02579 Document1-3 Filed06/10/15 Page35 of 64 US 8,398,546 B2 5 6 estimation for a certain meal based upon an average for that individual status parameter that cannot be directly detected by meal, duplication of a previous meal and a quick caloric any of the at least two sensors. estimate tool. A user is guided through the complex task of In either embodiment of the apparatus, the at least two recalling what they ate in order to increase compliance and reduce the discrepancy between self-reported and actual sensors may be both physiological sensors, or may be one 5 caloric intake. The combination of the information collected from the or wherein at least one of the sensors is separately located apparatus and the information entered by the user is used to provide feedback information regarding the user's progress and recommendations for reaching dietary goals. Because of from the housing. The apparatus may further include a flex10 ible body supporting the housing having first individual's body. The flexible make lifestyle changes to meet weight loss goals, such as body may support one or more of the sensors. The apparatus may further include wrapping adjusting diet or exercising to burn more calories. The system parameters including energy expenditure and caloric intake and second members that are adapted to wrap around a portion of the the accuracy of the information, the user can proactively can also predict data indicative of human physiological physiological sensor and one contextual sensor. The appara­ tus may further include a housing adapted to be worn on the individual's body, wherein the housing supports the sensors means coupled to the housing for maintaining contact 15 between the housing and the individual's body, and the wrap­ ping means may support one or more of the sensors. for any given relevant time period as well as other detected Either embodiment of the apparatus may further include a and derived physiological or contextual information. The user central monitoring unit remote from the at least two sensors may then be notified as to their actual or predicted progress that includes a data storage device. The data storage device with respect to the optimum energy balance or other goals for 20 receives the derived data from the processor and retrievably the day. stores the derived data therein. The apparatus also includes An apparatus is disclosed for monitoring certain identified means for transmitting information based on the derived data human status parameters which includes at least one sensor from the central monitoring unit to a recipient, which recipi­ adapted to be worn on an individual's body. A preferred ent may include the individual or a third party authorized by embodiment utilizes a combination of sensors to provide 25 the individual. The processor may be supported by a housing more accurately sensed data, with the output of the multiple adapted to be worn on the individual's body, or alternatively sensors being utilized in the derivation of additional data. The may be part of the central monitoring unit. sensor or sensors utilized by the apparatus may include a A weight-loss directed software program is disclosed that physiological sensor selected from the group consisting of automates the tracking of the energy expenditure of the indi- respiration sensors, temperature sensors, heat flux sensors, 30 vidual through the use ofthe apparatus and reduces the repeti- body conductance sensors, body resistance sensors, body tive nature of data entry in the determination of caloric con­ potential sensors, brain activity sensors, blood pressure sen­ sumption sors, body impedance sensors, body motion sensors, oxygen regarding the user's weight loss goals. The software program in addition to providing relevant feedback consumption sensors, body chemistry sensors, body position is based on the energy balance equation which has two com- sensors, body pressure sensors, light absorption sensors, 35 ponents: energy intake and eneigy expenditure. The differbody sound sensors, piezoelectric sensors, electrochemical ence between these two values is the energy balance. When sensors, strain gauges, and optical sensors. The sensor or this value is negative, a weight loss should be achieved sensors are adapted to generate data indicative of at least a because fewer calories were consumed than expended. A first parameter of the individual and a second parameter of the positive energy balance will most likely result in no loss of individual, wherein the first parameter is a physiological 40 weight or a weight gain, parameter. The apparatus also includes a processor that The weight-loss directed software program may include an receives at least a portion of the data indicative of the first energy intake tracking subsystem, an energy expenditure parameter and the second parameter. The processor is adapted tracking subsystem, a weight tracking subsystem and an to generate derived data from at least a portion of the data energy balance and feedback subsystem. indicative of a first parameter and a second parameter, 45 The energy intake tracking subsystem preferably incorpo­ wherein the derived data comprises a third parameter of the rates a food database which includes an extensive list of individual. The third parameter is an individual status param­ commonly consumed foods, common branded foods avail­ eter that cannot be directly detected by the at least one sensor. able at regional and national food chains, and branded off the In an alternate embodiment, the apparatus for monitoring shelf entrees and the nutrient information for each item. The human status parameters is disclosed that includes at least two 50 user also has the capability to enter custom preparations or sensors adapted to be worn on an individual's body selected recipes which then become a part of the food in the database. from the group consisting of physiological sensors and con­ The eneigy expenditure subsystem includes a data retrieval textual sensors, wherein at least one of the sensors is a physi­ process to retrieve the data from the apparatus. The system ological sensor. The sensors are adapted to generate data uses the data collected by the apparatus to determine total indicative of at least a first parameter of the individual and a 55 energy expenditure. The user has the option of manually second parameter of the individual, wherein the first param­ entering data for an activity engaged in during a time when the eter is physiological. The apparatus also includes a processor apparatus was not available. The system is further provided for receiving at least a portion of the data indicative of at least with the ability to track and recognize certain activity or a first parameter and a second parameter, the processor being nutritional intake parameters or patterns and automatically adapted to generate derived data from the data indicative of at 60 provide such identification to the user on a menu for selection, parameter and a second parameter. The derived as disclosed in copending U.S. patent application Ser. No. data comprises a third parameter of the individual, for least a first 10/682,293, the disclosure of which is incorporated by refer­ example one selected from the group consisting of ovulation ence. Additionally, the system may directly adopt such iden­ state, sleep state, calories burned, basal metabolic rate, basal tified activities or nutritional information without input from temperature, physical activity level, stress level, relaxation 65 the user, as appropriate, level, oxygen consumption rate, rise time, time in zone, The energy balance and feedback subsystem provides recovery time, and nutrition activity. The third parameter is an feedback on behavioral strategies to achieve eneigy balance Case3:15-cv-02579 Document1-3 Filed06/10/15 Page36 of 64 US 8,398,546 B2 7 proactively. A feedback and coaching engine analyzes the data generated by the system to provide the user with a variety of choices depending on the progress of the user. A management system is disclosed which includes an apparatus that continuously monitors a user's energy expenditure and a software platform for the manual input of infor­ mation by the user regarding physical activity and calories consumed. This manual input may be achieved by the user entering their own food, by a second party entering the food for them such as an assistant in a assisted living situation, or through a second party receiving the information from the user via voice, phone, or other transmission mechanism. Alternatively, the food intake can be automatically gathered through either a monitoring system that captures what food is removed from an storage appliance such as a refrigerator or inserted into a food preparation appliance such as an oven or through a derived measure from one or more physiological parameters. The system may be further adapted to obtain life activities data of the individual, wherein the information transmitted from the central monitoring unit is also based on the life activities data. The central monitoring unit may also be adapted to generate and provide feedback relating to the degree to which the individual has followed a suggested routine. The feedback may be generated from at least a portion of at least one of the data indicative of at least a first parameter and a second parameter, the derived data and the life activities data. The central monitoring unit may also be adapted to generate and provide feedback to a recipient relating to management of an aspect of at least one of the individual's health and lifestyle. This feedback may be generated from at least one of the data indicative of a first parameter, the data indica­ tive of a second parameter and the derived data. The feedback may include suggestions for modifying the individual's behavior. The system may be further adapted to include a weight and body fat composition tracking subsystem to interpret data received from: manual input, a second device such as a trans­ ceiver enabled weight measuring device, or data collected by the apparatus. The system may also be further adapted to include a meal planning subsystem that allows a user to customize a meal plan based on individual fitness and weightless goals. Appro­ priate foods are recommended to the user based on answers provided to general and medical questionnaires. These ques­ tionnaires are used as inputs to the meal plan generation system to ensure that foods are selected that take into consid­ eration specific health conditions or preferences of the user. The system may be provided with functionality to recommend substitution choices based on the food category and exchange values of the food and will match the caloric con­ tent between substitutions. The system may be further adapted to generate a list of food or diet supplement intake 8 vascular and resistance training.The recommendations could be based on the fitness goals submitted by the questionnaire to the system. The system may also provide feedback to the user in the 5 form of a periodic or intermittent status report. The status report may be an alert located in a box on a location of the screen and is typically set off to attract the user's attention. Status reports and images are generated by creating a key string based on the user's current view and state and may 10 provide information to the user about their weight loss goal progress. This information may include suggestions to meet the user's calorie balance goal for the day. Although this description addresses weight loss with speci­ ficity, it should be understood that this system may also be 15 equally applicable to weight maintenance or weight gain. BRIEF DESCRIPTION OF THE DRAWINGS 20 25 30 35 40 45 50 Further features and advantages of the present invention will be apparent upon consideration of the following detailed description of the present invention, taken in conjunction with the following drawings, in which like reference characters refer to like parts, and in which: FIG. 1 is a diagram of an embodiment of a system for monitoring physiological data and lifestyle over an electronic network according to the present invention; FIG. 2 is a block diagram of an embodiment of the sensor device shown in FIG. 1; FIG. 3 is a block diagram of an embodiment of the central monitoring unit shown in FIG. 1; FIG.4isablock diagram of an alternate embodiment of the central monitoring unit shown in FIG. 1; FIG. 5 is a representation of a preferred embodiment of the Health Manager web page according to an aspect of the present invention; FIG. 6 is a representation of a preferred embodiment of the nutrition web page according to an aspect of the present invention; FIG. 7 is an block diagram representing the configuration of the management system for a specific user according to an aspect of the present invention. FIG. 8 is a block diagram of a preferred embodiment of the weight tracking system according to an aspect of the present invention. FIG. 9 is a block diagram of a preferred embodiment of the update information wizard interface according to one aspect of the present invention. FIG. 10 is a representation of a preferred embodiment of the activity level web page according to an aspect of the present invention; FIG. 11 is a representation of a preferred embodiment of the mind centering web page according to an aspect of the recommendations based on answers provided by the user to a 55 present invention; FIG. 12 is a representation of a preferred embodiment of The system may also provide the option for the user to save the sleep web page according to an aspect of the present or print a report of summary data. The summary data could invention; provide detailed information about the daily eneigy intake, FIG. 13 is a representation of a preferred embodiment of daily energy expenditure, weight changes, body fat compo- 60 the daily activities web page according to an aspect of the sition changes and nutrient information if the user has been present invention; consistently logging the foods consumed. Reports containing FIG. 14 is a representation of a preferred embodiment of information for a certain time period, such as 7 days, 30 days, the Health Index web page according to an aspect of the 90 days and from the beginning of the system usage may also present invention; be provided. 65 FIG. 15 is a representation of a preferred embodiment of The system may also include an exercise planning sub­ the Weight Manager interface according to an aspect of the system that provides recommendations to the user for cardio­ present invention; questionnaire. Case3:15-cv-02579 Document1-3 Filed06/10/15 Page37 of 64 US 8,398,546 B2 9 10 FIG. 16 is a logical diagram illustrating the generation of intermittent status reports according to an aspect of the present invention; FIG. 17 is a logical diagram illustrating the generation of an intermittent status report based on energy expenditure values according to an aspect of the present invention; FIG. 18 is a logical diagram illustrating the generation of an intermittent status report based on caloric intake in addi­ tion to state status determination according to an aspect of the present invention; FIG. 19 is a logical diagram illustrating the calculation of state determination according to an aspect of the present invention; FIG. 20 is a front view of a specific embodiment of the sensor device shown in FIG. 1; FIG. 21 is a back view of a specific embodiment of the sensor device shown in FIG. 1; FIG. 22 is a side view of a specific embodiment of the sensor device shown in FIG. 1; FIG. 23 is a bottom view of a specific embodiment of the sensor device shown in FIG. 1; FIGS. 24 and 25 are front perspective views of a specific embodiment of the sensor device shown in FIG. 1; FIG. 26 is an exploded side perspective view of a specific embodiment of the sensor device shown in FIG. 1; FIG. 27 is a side view of the sensor device shown in FIGS. 20 through 26 inserted into a battery recharger unit; and FIG. 28 is a block diagram illustrating all of the compo­ nents either mounted on or coupled to the printed circuit board forming a part of the sensor device shown in FIGS. 20 ' ' 26. ~~ through FIG. 29 is a block diagram showing the format of algo­ rithms that are developed according to anaspect of the present invention; and FIG. 30 is a block diagram illustrating an example algorithm for predicting energy expenditure according to the present invention. parameters of an individual is collected and transmitted, either subsequently or in real-time, to a site, preferably remote from the individual, where it is stored for later manipulation and presentation to a recipient, preferably over an electronic network such as the Internet. Contextual param­ eters as used herein means parameters relating to activity state or to the environment, surroundings and location of the indi­ vidual, including, but not limited to, air quality, sound quality, ambient temperature, global positioning and the like. Refer­ ring to FIG.l, located at user location 5 is sensor device 10 adapted to be placed in proximity with at least a portion of the human body. Sensor device 10 is preferably worn by an individual user on his or her body, for example as part of a garment such as a form fitting shirt, or as part of an arm band or the like. Sensor device 10, includes one or more sensors, which are adapted to generate signals in response to physi­ ological characteristics of an individual, and a microproces­ sor. Proximity as used herein means that the sensors of sensor device 10 are separated from the individual's body by a mate­ rial or the like, or a distance such that the capabilities of the sensors are not impeded. Sensor device 10 generates data indicative of various physiological parameters of an individual, such as the indi­ vidual's heart rate, pulse rate, beat-to-beat heart variability, EKG or ECG, respiration rate, skin temperature, core body temperature, heat flow off the body, galvanic skin response or GSR, EMG, EEG, EOG, blood pressure, body fat, hydration level, activity level, oxygen consumption, glucose or blood sugar level, body position, pressure on muscles or bones, and UV radiation exposure and absorption. In certain cases, the data indicative of the various physiological parameters is the signal or signals themselves generated by the one or more sensors and in certain other cases the data is calculated by the microprocessor based on the signal or signals generated by the one or more sensors. Methods for generating data indicative of various physiological parameters and sensors to be used therefor are well known. Table 1 provides several examples of such well known methods and shows the param­ eter in question, an example method used, an example sensor device used, and the signal that is generated. Table 1 also provides an indication as to whether further processing based on the generated signal is required to generate the data. 5 10 15 20 25 30 35 DESCRIPTION OF THE PREFERRED EMBODIMENTS In general, according to the present invention, data relating to the physiological state, the lifestyle and certain contextual TABLE 1 Parameter Example Method Example Sensor Signal Further Processing Heart Rate Pulse Rate EKG BVP DC Voltage Change in Resistance Yes Yes Beat-to-Beat Variability EKG Heart Beats 2 Electrodes LED Emitter and Optical Sensor 2 Electrodes DC Voltage Yes Skin Surface Potentials 3-10 Electrodes DC Voltage Respiration Rate Chest Volume Change Surface Temperature Probe Esophageal or Rectal Probe Heat Flux Skin Conductance Strain Gauge Change in Resistance No* (depending on location) Yes Thermistors Change in Resistance Yes Thermistors Change in Resistance Yes Thermopile 2 Electrodes DC Voltage Conductance Yes No Skin Surface Potentials Skin Surface Potentials 3 Electrodes DC Voltage No Multiple Electrodes DC Voltage Yes Skin Temperature Core Temperature Heat Flow Galvanic Skin Response EMG EEG Case3:15-cv-02579 Document1-3 Filed06/10/15 Page38 of 64 US 8,398,546 B2 11 12 TABLE 1-continued Parameter Example Method Example Sensor Signal Further Processing EOG Eye Movement DC Voltage Yes Blood Pressure Non-Invasive Korotkuff Sounds Body Impedance Body Movement Thin Film Piezoelectric Sensors Electronic Sphygromarometer 2 Active Electrodes Accelerometer Change in Resistance Yes Yes Yes Oxygen Consumption Glucose Level Body Position (e.g. supine, erect, sitting) Muscle Pressure Oxygen Uptake Electro-chemical Change in Impedance DC Voltage, Capacitance Changes DC Voltage Change Non-Invasive N/A Electro-chemical Mercury Switch Array DC Voltage Change DC Voltage Change Yes Yes N/A DC Voltage Change Yes UV Radiation Absorption N/A Thin Film Piezoelectric Sensors UV Sensitive Photo Cells DC Voltage Change Yes Body Fat Activity It is to be specifically noted that a number of other types and categories of sensors may be utilized alone or in conjunc­ tion with those given above, including but not limited to relative and global positioning sensors for determination of location of the user; torque & rotational acceleration for determination of orientation in space; blood chemistry sen­ sors; interstitial fluid chemistry sensors; bio-impedance sen­ sors; and several contextual sensors, such as: pollen, humid­ ity, ozone, acoustic, body and ambient noise and sensors adapted to utilize the device in a biofingerprinting scheme. The types of data listed in Table 1 are intended to be examples of the types of data that can be generated by sensor device 10. It is to be understood that other types of data relating to other parameters can be generated by sensor device 10 without departing from the scope of the present invention. 25 30 Yes The microprocessor of sensor device 10 may be pro­ grammed to summarize and analyze the data. For example, the microprocessor can be programmed to calculate an aver­ age, minimum or maximum heart rate or respiration rate over a defined period of time, such as ten minutes. Sensor device 10 may be able to derive information relating to an individu­ al's physiological state based on the data indicative of one or more physiological parameters. The microprocessor of sen­ sor device 10 is programmed to derive such information using known methods based on the data indicative of one or more physiological parameters. Table 2 provides examples of the type of information that can be derived, and indicates some of the types of data that can be used therefor. TABLE 2 Derived Information Example Input Data Signals Ovulation Sleep onset/wake Skin temperature, core temperature, oxygen consumption Beat-to-beat variability, heart rate, pulse rate, respiration rate, skin temperature, core temperature, heat flow, galvanic skin response, EMG, EEG, EOG, blood pressure, oxygen consumption Heart rate, pulse rate, respiration rate, heat flow, activity, oxygen consumption Heart rate, pulse rate, respiration rate, heat flow, activity, oxygen consumption Skin temperature, core temperature Heart rate, pulse rate, respiration rate, heat flow, activity, oxygen consumption EKG, beat-to-beat variability, heart rate, pulse rate, respiration rate, skin temperature, heat flow, galvanic skin response, EMG, EEG, blood pressure, activity, oxygen consumption EKG, beat-to-beat variability, heart rate, pulse rate, respiration rate, skin temperature, heat flow, galvanic skin response, EMG, EEG, blood pressure, activity, oxygen consumption EKG, heart rate, pulse rate, respiration rate, heat flow, blood pressure, activity, oxygen consumption Heart rate, pulse rate, heat flow, oxygen consumption Calories burned Basal metabolic rate Basal temperature Activity level Stress level Relaxation level Maximum oxygen consumption rate Rise time or the time it takes to rise from a resting rate to 85% of a target maximum Time in zone or the time heart rate was above 85% of a target maximum Recovery time or the time it takes heart rate to return to a resting rate after heart rate was above 85% of a target maximum Heart rate, pulse rate, heat flow, oxygen consumption Heart rate, pulse rate, heat flow, oxygen consumption Case3:15-cv-02579 Document1-3 Filed06/10/15 Page39 of 64 US 8,398,546 B2 13 14 Additionally, sensor device 10 may also generate data indicative of various contextual parameters relating to activ­ ity state or the environment surrounding the individual. For example, sensor device 10 can generate data indicative of the air quality, sound level/quality, light quality or ambient temperature near the individual, or even the motion or global positioning of the individual. Sensor device 10 may include one or more sensors for generating signals in response to contextual characteristics relating to the environment sur­ rounding the individual, the signals ultimately being used to generate the type of data described above. Such sensors are well known, as are methods for generating contextual para­ metric data such as air quality, sound level/quality, ambient temperature and global positioning. FIG. 2 is a block diagram of an embodiment of sensor device 10. Sensor device 10 includes at least one sensor 12 and microprocessor 20. Depending upon the nature of the signal generated by sensor 12, the signal can be sent through one or more of amplifier 14, conditioning circuit 16, and analog-to-digital converter 18, before being sent to microprocessor 20. For example, where sensor 12 generates an analog signal in need of amplification and filtering, that signal can be sent to amplifier 14, and then on to conditioning circuit 16, which may, for example, be a band pass filter. The amplified and conditioned analog signal can then be transferred to analog-to-digital converter 18, where it is converted to a digital signal. The digital signal is then sent to microprocessor 20. Alternatively, if sensor 12 generates a digital signal, that signal can be sent directly to microprocessor 20. A digital signal or signals representing certain physiological and/or contextual characteristics of the individual user may be used by microprocessor 20 to calculate or generate data indicative of physiological and/or contextual parameters of the individual user. Microprocessor 20 is programmed to derive information relating to at least one aspect of the individual's physiological state. It should be understood that microprocessor 20 may also comprise other forms of proces­ sors or processing devices, such as a microcontroller, or any other device that can be programmed to perform the function­ ality described herein. Optionally, central processing unit may provide opera­ tional control or, at a minimum, selection of an audio player device 21.As will be apparent to those skilled in the art, audio player 21 is of the type which either stores and plays or plays separately stored audio media. The device may control the output of audio player 21, as described in more detail below, or may merely furnish a user interface to permit control of audio player 21 by the wearer. The data indicative of physiological and/or contextual parameters can, according to one embodiment of the present invention, be sent to memory 22, such as flash memory, where it is stored until uploaded in themanner to be described below. Although memory 22 is shown in FIG. 2 as a discrete element, it will be appreciated that it may also be part of microproces­ sor 20. Sensor device 10 also includes input/output circuitry 24, which is adapted to output and receive as input certain data signals in the manners to be described herein. Thus, memory 22 of the sensor device 10 will build up, over time, a store of data relating to the individual user's body and/or environment. That data is periodically uploaded from sensor device 10 and sent to remote central monitoring unit 30, as shown in FIG. 1, where it is stored in a database for subse­ quent processing and presentation to the user, preferably through a local or global electronic network such as the Inter­ net. This uploading of data can be an automatic process that is initiated by sensor device10 periodically or upon the happen­ ing of an event such as the detection by sensor device 10 of a heart rate below a certain level, or can be initiated by the individual user or some third party authorized by the user, preferably according to some periodic schedule, such as every day at 10:00 p.m. Alternatively, rather than storing data in memory 22, sensor device 10 may continuously upload data in real time. The uploading of data from sensor device 10 to central monitoring unit 3 0 for storage can beaccomplished in various ways. In one embodiment, the data collected by sensor device 10 is uploaded by first transferring the data to personal com­ puter 35 shown in FIG. 1 by means of physical connection 40, which, for example, may be a serial connection such as an RS232 or USB port. This physical connection may also be accomplished by using a cradle, not shown, that is electronically coupled to personal computer 35 into which sensor device 10 can be inserted, as is common with many commer­ cially available personal digital assistants. The uploading of data could be initiated by then pressing a button on the cradle or could be initiated automatically upon insertion of sensor device 10 or upon proximity to a wireless receiver. The data collected by sensor device 10 may be uploaded by first trans­ ferring the data to personal computer 35 by means of shortrange wireless transmission, such as infrared or RF transmis­ sion, as indicated at 45. Once the data is received by personal computer 35, it is optionally compressed and encrypted by any one of a variety of well known methods and then sent out over a local or global electronic network, preferably the Internet, to central moni­ toring unit 30. It should be noted that personal computer 35 can be replaced by any computing device that has access to and that can transmit and receive data through the electronic network, such as, for example, a personal digital assistant such as the Palm VII sold by Palm, Inc., or the Blackberry 2-way pager sold by Research in Motion, Inc. Alternatively, the data collected by sensor device 10, after being encrypted and, optionally, compressed by microproces­ sor 20, may be transferred to wireless device 50, such as a 2-way pager or cellular phone, for subsequent long distance wireless transmission to local telco site 55 using a wireless protocol such as e-mail or as ASCII or binary data. Local telco site 55 includes tower 60 that receives the wireless transmission from wireless device 50 and computer 65 connected to tower 60. According to the preferred embodiment, computer 65 has access to the relevant electronic network, such as the Internet, and is used to transmit the data received in the form of the wireless transmission to the central monitoring unit 30 over the Internet. Although wireless device 50 is shown in FIG. 1 as a discrete device coupled to sensor device 10, it or a device having the same or similar functionality may be embedded as part of sensor device 10. Sensor device 10 may be provided with a button to be used to time stamp events such as time to bed, wake time, and time of meals. These time stamps are stored in sensor device 10 and are uploaded to central monitoring unit 30 with the rest of the data as described above. The time stamps may include a digitally recorded voice message that, after being uploaded to central monitoring unit 30, are translated using voice recog­ nition technology into text or some other information format that can be used by central monitoring unit 30. Note that in an alternate embodiment, these time-stamped events can be automatically detected. In addition to using sensor device 10 to automatically collect physiological data relating to an individual user, a kiosk could be adapted to collect such data by, for example, weighing the individual, providing a sensing device similar to sensor device 10 on which an individual places his or her hand or another part of his or her body, or by scanning the indi- 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page40 of 64 US 8,398,546 B2 15 16 vidual's body using, for example, laser technology or an iStat using the keypad or by voice/voice recognition technology. blood analyzer. The kiosk would be provided with processing Central monitoring unit 30 may also be given access to a capability as described herein and access to the relevant elec­ source of information controlled by the user, for example the tronic network, and would thus be adapted to send the col­ user's electronic calendar such as that provided with the lected data to the central monitoring unit 30 through the 5 Outlook product sold by Microsoft Corporation of Redmond, electronic network.A desktop sensing device, again similar to Wash., from which it could automatically collect information. sensor device 10, on which an individual places his or her The data relating to life activities may relate to the eating, hand or another part of his or her body may also be provided. sleep, exercise, mind centering or relaxation, and/or daily living habits, patterns and/or activities of the individual. For example, such a desktop sensing device could be a blood pressure monitor in which an individual places his or her arm. 10 Thus, sample questions may include: What did you have for lunch today? What time did you go to sleep last night? What An individual might also wear a ring having a sensor device time did you wake up this morning? How long did you run on 10 incorporated therein. A base, not shown, could then be the treadmill today? provided which is adapted to be coupled to the ring. The desktop sensing device or the base just described may then be Feedback may also be provided to a user directly through coupled to a computer such as personal computer 35 by 15 sensor device 10 in a visual form, for example through an means of a physical or short range wireless connection so that LED or LCD or by constructing sensor device 10, at least in the collected data could be uploaded to central monitoring part, of a thermochromatic plastic, in the form of an acoustic unit 30 over the relative electronic network in the manner signal or in the form of tactile feedback such as vibration. described above. A mobile device such as, for example, a Such feedback may be a reminder or an alert to eat a meal or personal digital assistant, might also be provided with a sen- 20 take medication or a supplement such as a vitamin, to engage in an activity such as exercise or meditation, or to drink water sor device 10 incorporated therein. Such a sensor device 10 when a state of dehydration is detected. Additionally, a would beadapted to collect data when mobiledevice is placed reminder or alert can be issued in the event that a particular in proximity with the individual's body, such as by holding physiological parameter such as ovulation has been detected, the device in the palm of one's hand, and upload the collected data to central monitoring unit 30 in any of the ways described 25 a level of calories burned during a workout has been achieved or a high heart rate or respiration rate has been encountered. herein. An alternative embodiment includes the incorporation of As will be apparent to those of skill in the art, it may be third party devices, not necessary worn on the body, collect possible to download data from central monitoring unit 30 to additional data pertaining to physiological conditions. sensor device10. The flow of data in such a download process Examples include portable blood analyzers, glucose moni- 30 would be substantially the reverse of that described above tors, weight scales, blood pressure cuffs, pulse oximeters, with respect to the upload of data from sensor device 10. CPAP machines, portable oxygen machines, home thermo­ Thus, it is possible that the firmware of microprocessor 20 of stats, treadmills, cell phones and GPS locators. The system sensor device 10 can be updated or altered remotely, i.e., the could collect from, or in the case of a treadmill or CPAP, microprocessor can be reprogrammed, by downloading new control these devices, and collect data to be integrated into the 35 firmware to sensor device 10 from central monitoring unit 30 for such parameters as timing and sample rates of sensor streams for real time or future derivations of new parameters. An example of this is a pulse oximeter on the user's finger device 10. Also, the reminders/alerts provided by sensor could help measure pulse and therefore serve a surrogate device 10 may be set by the user using the web site maintained reading for blood pressure. Additionally, a user could utilize by central monitoring unit 30 and subsequently downloaded one of these other devices to establish baseline readings in 40 to the sensor device 10. order to calibrate the device. Referring to FIG. 3, a block diagram of an embodiment of Furthermore, in addition to collecting data by automati­ central monitoring unit 30 is shown. Central monitoring unit cally sensing such data in the manners described above, indi­ 30 includes CSU/DSU 70 which is connected to router 75, the viduals can also manually provide data relating to various life main function of which is to take data requests or traffic, both activities that is ultimately transferred to and stored at central 45 incoming and outgoing, and direct such requests and traffic monitoring unit 30. An individual user can access a web site for processing or viewing on the web site maintained by central monitoring unit 30. Connected to router 75 is firewall maintained by central monitoring unit 30 and can directly 80. The main purpose of firewall 80 is to protect the remainder input information relating to life activities by entering text of central monitoring unit 30 from unauthorized or malicious freely, by responding to questions posed by the web site, or by clicking through dialog boxes provided by the web site. Cen- 50 intrusions. Switch 85, connected to firewall 80, is used to direct data flow between middleware servers 95a through 95c tral monitoring unit 30 can also be adapted to periodically and database server 110. Load balancer 90 is provided to send electronic mail messages containing questions designed spread the workload of incoming requests among the identi­ to elicit information relating to life activities to personal computer 35 or to some other device that can receive elec­ cally configured middleware servers 95a through 95c. Load tronic mail, such as a personal digital assistant, a pager, or a 55 balancer 90, a suitable example of which is the F5 Serverlron cellular phone. The individual would then provide data relat­ product sold by Foundry Networks, Inc. of San Jose, Calif, ing to life activities to central monitoring unit 30 by respond­ analyzes the availability of each middleware server 95a through 95c, and the amount of system resources being used ing to the appropriate electronic mail message with the rel­ evant data. Central monitoring unit 30 may also be adapted to in each middleware server 95a through 95c, in order to spread place a telephone call to an individual user in which certain 60 tasks among them appropriately, questions would be posed to the individual user. The user Central monitoring unit 30 includes network storage could respond to the questions by entering information using device 100, such as a storage area network or SAN, whichacts a telephone keypad, or by voice, in which case conventional as the central repository for data. In particular, network stor­ voice recognition technology would be used by central moni­ age device 100 comprises a database that stores all data gathtoring unit 30 to receive and process the response. The tele- 65 ered for each individual user in the manners described above, phone call may also be initiated by the user, in which case the An example of a suitable network storage device 100 is the user could speak to a person directly or enter information Symmetrix product sold by EMC Corporation of Hopkinton, Case3:15-cv-02579 Document1-3 Filed06/10/15 Page41 of 64 US 8,398,546 B2 17 18 Mass. Although only one network storage device 100 is shown in FIG. 3, it will be understood that multiple network storage devices of various capacities could be used depending on the data storage needs of central monitoring unit 30. Cen­ tral monitoring unit 30 also includes database server 110 which is coupled to network storage device 100. Database server 110 is made up of two main components: a large scale multiprocessor server and an enterprise type software server component such as the 8/8i component sold by Oracle Cor­ poration of Redwood City, Calif, or the 506 7 component sold by Microsoft Corporation of Redmond, Wash. The pri­ mary functions of database server 110 are that of providing access upon request to the data stored in network storage device 100, and populating network storage device 100 with new data. Coupled to network storage device 100 is controller 115, which typically comprises a desktop personal computer, for managing the data stored in network storage device 100. Middleware servers 95a through 95c, a suitable example of which is the220R Dual Processor soldby Sun Microsystems, Inc. of Palo Alto, Calif, each contain software for generating and maintaining the corporate or home web page or pages of the web site maintained by central monitoring unit 30. As is known in the art, a web page refers to a block or blocks of data available on the World-Wide Web comprising a file or files written in Hypertext Markup Language or HTML, and a web site commonly refers to any computer on the Internet running a World-Wide Web server process. The corporate or home web page or pages are the opening or landing web page or pages that are accessible by all members of the general public that visit the site by using the appropriate uniform resource locator or URL. As is known in the art, URLs are the form of address used on the World-Wide Web and provide a standard way of specifying the location of an object, typically a web page, on the Internet. Middleware servers 95a through 95c also each contain software for generating and maintaining the web pages of the web site of central monitoring unit 30 that can only be accessed by individuals that register and become members of central monitoring unit 30. The member users will be those individuals who wish to have their data stored at central monitoring unit 30. Access by such member users is controlled using passwords for security purposes. Preferred embodiments of those web pages are described in detail below and are generated using collected data that is stored in the database of network storage device 100. Middleware servers 95a through 95c also contain software for requesting data from and writing data to network storage device 100 through database server 110. When an individual user desires to initiate a session with the central monitoring unit 30 for the purpose of entering data into the database of network storage device100, viewing his or her data stored in the database of network storage device 100, or both, the user visits the home web page of central monitoring unit 30 using a browser program such as Internet Explorer distributed by Microsoft Corporation of Redmond, Wash., and logs in as a registered user. Load balancer 90 assigns the user to one of the middleware servers 95a through 95c, identified as the chosen middleware server. A user will preferably be assigned to a chosen middleware server for each entire session. The chosen middleware server authenticates the user using any one of many well known methods, to ensure that only the true user is permitted to access the information in the database. A mem­ ber user may also grant access to his or her data to a thirdparty such as a health care provider or a personal trainer. Each authorized third party may be given a separate password and may view the member user's data using a conventional browser. It is therefore possible for both the user and the third party to be the recipient of the data. When the user is authenticated, the chosen middleware server requests, through database server 110, the individual user's data from network storage device 100 for a predeter­ mined time period. The predetermined time period is prefer­ ably thirty days. The requested data, once received from network storage device 100, is temporarily stored by the chosen middleware server in cache memory. The cached data is used by the chosen middleware server as the basis for presenting information, in the form of web pages, to the user again through the user's browser. Each middleware server 95a through 95c is provided with appropriate software for generating such web pages, including software for manipu­ lating and performing calculations utilizing the data to put the data in appropriate format for presentation to the user. Once the user ends his or her session, the data is discarded from cache. When the user initiates a new session, the process for obtaining and caching data for that user as described above is repeated. This caching system thus ideally requires that only one call to the network storage device 100 be made per session, thereby reducing the traffic that database server 110 must handle. Should a request from a user during a particular session require data that is outside of a predetermined time period of cached data already retrieved, a separate call to network storage device 100 may be performed by the chosen middleware server. The predetermined time period should be chosen, however, such that such additional calls are mini­ mized. Cached data may also be saved in cache memory so that it can be reused when a user starts a new session, thus eliminating the need to initiate a new call to network storage device 100. As described in connection with Table 2, the microproces­ sor of sensor device 10 may be programmed to derive infor­ mation relating to an individual's physiological state based on the data indicative of one or more physiological parameters, Central monitoring unit 30, and preferably middleware serv­ ers 95a through 95c, may also be similarly programmed to derive such information based on the data indicative of one or more physiological parameters. It is also contemplated that a user will input additional data during a session, for example, information relating to the user's eating or sleeping habits. This additional data is pref­ erably stored by the chosen middleware server in a cache during the duration of the user's session. When the user ends the session, this additional new data stored in a cache is transferred by the chosen middleware server to database server 110 for population in network storage device 100. Alternatively, in addition to being stored in a cache for poten­ tial use during a session, the input data may also be immediately transferred to database server 110 for population in network storage device 100, as part of a write-through cache system which is well known in the art. Data collected by sensor device 10 shown in FIG. 1 is periodically uploaded to central monitoring unit 30. Either by long distance wireless transmission or through personal computer 35, a connection to central monitoring unit 30 is made through an electronic network, preferably the Internet. In particular, connection is made to load balancer 90 through CSU/DSU 70, router 75, firewall 80 and switch 85. Load balancer 90 then chooses one of the middleware servers 95a through 95c to handle the upload of data, hereafter called the chosen middleware server. The chosen middleware server authenticates the user using any one of many well known methods. If authentication is successful, the data is uploaded to the chosen middleware server as described above, and is ultimately transferred to databaseserver 110 for populationin the network storage device 100. 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page42 of 64 US 8,398,546 B2 19 20 Referring to FIG. 4, an alternate embodiment of central monitoring unit 30 is shown. In addition to the elements shown and described with respect to FIG. 3, the embodiment of the central monitoring unit 30 shown in FIG. 4 includes a mirror network storage device 120 which is a redundant backup of network storage device 100. Coupled to mirror network storage device 120 is controller 122. Data from net­ work storage device 100 is periodically copied to mirror network storage device 120 for data redundancy purposes. Third parties such as insurance companies or research institutions may be given access, possibly for a fee, to certain of the information stored in mirror network storage device 120. Preferably, in order to maintain the confidentiality of the individual users who supply data to central monitoring unit 30, these third parties are not given access to such user's individual database records, but rather are only given access to the data stored in mirror network storage device 120 in aggregate form. Such third parties may be able to access the information stored in mirror network storage device 120 through the Internet using a conventional browser program. Requests from third parties may come in through CSU/DSU 70, router 75, firewall 80 and switch 85. In the embodiment shown in FIG. 4, a separate load balancer130 is provided for spreading tasks relating to the accessing and presentation of data from mirror drive array 120 among identically configured middleware servers 135a through 135c. Middleware servers 135a through 135c each contain software forenabling the third parties to, using a browser, formulate queries for information from mirror network storage device 120 through separate database server 125. Middleware servers 135a through 135c also contain software for presenting the infor­ mation obtained from mirror network storage device 120 to the third parties over the Internet in the form of web pages. In addition, the third parties can choose from a series of prepared reports that have information packaged along subject matter lines, such as various demographic categories. As will be apparent to one of skill in the art, instead of giving these third parties access to the backup data stored in mirror network storage device 120, the third parties may be given access to the data stored in network storage device 100. Also, instead of providing load balancer 130 and middleware servers 135a through 135c, the same functionality, although at a sacrificed level of performance, could be provided by load balancer 90 and middleware servers 95a through 95c. When an individual user first becomes a registered user or member, that user completes a detailed survey. The purposes of the survey are to: identify unique characteristics/circum­ stances for each user that they might need to address in order to maximize the likelihood that they will implement and maintain a healthy lifestyle as suggested by central monitoring unit 30; gather baseline data which will be used to set initial goals for the individual user and facilitate the calcula­ tion and display of certain graphical data output such as the Health Index pistons; identify unique user characteristics and circumstances that will help central monitoring unit 30 customize the type of content provided to the user in the Health Manager's Daily Dose; and identify unique user characteris­ tics and circumstances that the Health Manager can guide the user to address as possible barriers to a healthy lifestyle through the problem-solving function of the Health Manager. In an alternative embodiment specifically directed to a weight loss or management application, as more fully described herein, a user may elect to wear the sensor device 10 long term or continuously in order to observe changes in certain health or weight related parameters. Alternatively, the user may elect to only wear the sensor device 10 for a brief, initial period of time in order to establish a baseline or initial evaluation of their typical daily caloric intake and energy expenditure. This information may form the basis for diet and/or exercise plans, menu selections, meal plans and the like, and progress may be checked periodically by returning to use of the sensor device10 for brief periods within the time frame established for the completion of any relevant weight loss or change goal. The specific information to be surveyed may include: key individual temperamental characteristics, including activity level, regularity of eating, sleeping, and bowel habits, initial response to situations, adaptability, persistence, threshold of responsiveness, intensity of reaction, and quality of mood; the user's level of independent functioning, i.e., self-organization and management, socialization, memory, and academic achievement skills; the user's ability to focus and sustain attention, including the user's level of arousal, cognitive tempo, ability to filter distractions, vigilance, and self-moni­ toring; the user's current health status including current weight, height, and blood pressure, most recent general physician visit, gynecological exam, and other applicable physician/healthcare contacts, current medications and supple­ ments, allergies, and a review of current symptoms and/or health-related behaviors; the user's past health history, i.e., illnesses/surgeries, family history, and social stress events, such as divorce or loss of a job, that have required adjustment by the individual; the user's beliefs, values and opinions about health priorities, their ability to alter their behavior and, what might contribute to stress in their life, and how they manage it; the user's degree of self-awareness, empathy, empowerment, and self-esteem, and the user's current daily routines for eating, sleeping, exercise, relaxation and com­ pleting activities of daily living; and the user's perception of the temperamental characteristics of two key persons in their life, for example, their spouse, a friend, a co-worker, or their boss, and whether there are clashes present in their relationships that might interfere with a healthy lifestyle or contribute to stress. In the weight loss or management application, an indi­ vidual user first becomes a registered user or member of a software platform and is issued a body monitoring apparatus that collects data from the user. The user may further person­ alize the apparatus by input of specific information into the software platform. This information may include: name, birth date, height, weight, gender, waistline measurements, body type, smoker/nonsmoker, lifestyle, typical activities, usual bed time and usual wake time. After the user connects the apparatus to a personal computer or other similar device by any of the means of the connectivity described above, the apparatus configuration is updated with this information. The user may also have the option to set a reminder which may be a reminder to take a vitamin at a certain time, to engage in physical activity, or to upload data. After the configuration process is complete, the program displays how the device should be worn on the body, and the user removes the appa­ ratus from the personal computer for placement of the apparatus in the appropriate location on the body for the collection of data. Alternatively, some of this personalization can hap­ pen through an initial trial wearing period. In the more generally directed embodiments, each member user will have access, through the home web page of central monitoring unit 30, to a series of web pages customized for that user, referred to as the Health Manager. The opening Health Manager web page150 is shown in FIG. 5.The Health Manager web pages are the main workspace area for the member user. The Health Manager web pages comprise a utility through which central monitoring unit 30 provides various types and forms of data, commonly referred to as 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page43 of 64 US 8,398,546 B2 21 22 analytical status data, to the user that is generated from the the user comprises the time and duration of breakfast, lunch, data it collects or generates, namely one or more of: the data dinner and any snacks, and the foods eaten, the supplements such as vitamins that are taken, and the waterand other liquids indicative of various physiological parameters generated by consumed during a relevant, pre-selected time period. Based sensor device 10; the data derived from the data indicative of various physiological parameters; the data indicative of vari- 5 upon this data and on stored data relating to known properties ous contextual parameters generated by sensor device 10; and of various foods, central monitoring unit 30 calculates well the data input by the user. Analytical status data is character­ known nutritional food values such as calories and amounts ized by the application of certain utilities or algorithms to of proteins, fats, carbohydrates, vitamins, etc., consumed. convert one or more of the data indicative of various physi­ The Nutrition Health Index piston level is preferably deterological parameters generated by sensor device 10, the data 10 mined with respect to the following suggested healthy daily derived from the data indicative of various physiological routine: eat at least three meals; eat a varied diet consisting of parameters, the data indicative of various contextual param­ 6-11 servings of bread, pasta, cereal, and rice, 2-4 servings eters generated by sensor device 10, and the data input by the fruit, 3-5 servings of vegetables, 2-3 servings of fish, meat, user into calculated health, wellness and lifestyle indicators. poultry, dry beans, eggs, and nuts, and 2-3 servings of milk, For example, based on data input by the user relating to the 15 yogurt and cheese; and drink 8 or more 8 ounce glasses of foods he or she has eaten, things such as calories and amounts water. This routine may be adjusted based on information of proteins, fats, carbohydrates, and certain vitamins can be about the user, such as sex, age, height and/or weight. Certain calculated. As another example, skin temperature, heart rate, nutritional taigets may also be set by the user or for the user, respiration rate, heat flow and/or GSR can be used to provide relating to daily calories, protein, fiber, fat, carbohydrates, an indicator to the user of his or her stress level over a desired 20 and/or water consumption and percentages of total consumption. Parameters utilized in the calculation of the relevant time period. As still another example, skin temperature, heat piston level include the number of meals per day, the number flow, beat-to-beat heart variability, heart rate, pulse rate, res­ of glasses of water, and the types and amounts of food eaten piration rate, core temperature, galvanic skin response, EMG, EEG, EOG, blood pressure, oxygen consumption, ambient each day as input by the user. sound and body movement or motion as detected by a device 25 Nutritional information is presented to the user through such as an accelerometer can be used to provide indicators to nutrition web page 160 as shown in FIG. 6. The preferred the user of his or her sleep patterns over a desired time period. nutritional web page 160 includes nutritional fact charts 165 Located on the opening Health Manager web page 150 is and 170 which illustrate actual and taiget nutritional facts, Health Index 155. Health Index 155 is a graphical utility used respectively as pie charts, and nutritional intake charts 175 to measure and provide feedback to member users regarding 30 and 180 which show total actual nutritional intake and taiget their performance and the degree to which they have suc­ nutritional intake, respectively as pie charts. Nutritional fact ceeded in reaching a healthy daily routine suggested by cen­ charts 165 and 170 preferably show a percentage breakdown of items such as carbohydrates, protein and fat, and nutri­ tral monitoring unit 30. Health Index 155 thus provides an indication for the member user to track his or her progress. tional intake charts 175 and 180 are preferably broken down Health Index 155 includes six categories relating to the user's 35 to show components such as total and target calories, fat, carbohydrates, protein, and vitamins. Web page 160 also health and lifestyle: Nutrition, Activity Level, Mind Center­ includes meal and water consumption tracking 185 with time ing, Sleep, Daily Activities andHowYou Feel. The Nutrition entries, hyperlinks190 which allow the userto directly access category relates to what, when and how much a person eats nutrition-related news items and articles, suggestions for and drinks. The Activity Level category relates to how much a person moves around. The Mind Centering category relates 40 refining or improving daily routine with respect to nutrition and affiliate advertising elsewhere on the network, and cal­ to the quality and quantity of time a person spends engaging endar 195 for choosing between views having variable and in some activity that allows the body to achieve a state of selectable time periods. The items shown at 190 may be profound relaxation while the mind becomes highly alert and focused. The Sleep category relates to the quality and quantity selected and customized based on information learned about of a person's sleep. The Daily Activities category relates to 45 the individual in the survey and on their performance as measured by the Health Index. the daily responsibilities and health risks people encounter. Finally, the How You Feel category relates to the general In the weight management embodiment, a user may also perception that a person has about how they feel on a particu­ have access through central monitoring unit 30 to a software lar day. Each category has an associated level indicator or platform referred to as the Weight Manager which may be piston that indicates, preferably on a scale ranging from poor 50 included in the Health Manager module or independent. It is to excellent, how the user is performing with respect to that also contemplated that Weight Manager may be a web-based category. application. When each member user completes the initial survey When the Weight Manager software platform is initialized, described above, a profile is generated that provides the user a registered user may login to the Weight Manager. If a user is with a summary of his or her relevant characteristics and life 55 not registered, they must complete the registration process circumstances. A plan and/or set of goals is provided in the before using another part of the software platform. The user form of a suggested healthy daily routine. The suggested begins the registration process by selecting a user name and healthy daily routine may include any combination of specific password and entering the serial number of the apparatus. suggestions for incorporating proper nutrition, exercise, mind FIG. 7 is a block diagram illustrating the steps used to centering, sleep, and selected activities of daily living in the 60 configure the personalized Weight Manager. During the iniuser's life. Prototype schedules may be offered as guides for tial configuration of the Weight Manager, the user may per­ how these suggested activities can be incorporated into the sonalize the system with specific information in the user user's life. The user may periodically retake the survey, and profile 1000 of the Weight Manager. The user may also return based on the results, the items discussed above will be to the user profile 1000 at any time during the use of the adjusted accordingly. 65 system to modify the information. On the body parameters The Nutrition category is calculated from both data input screen 1005 the user may enter specific information includ­ ing: name, birth date, height, weight, sex, waistline measureby the user and sensed by sensor device 10. The data input by Case3:15-cv-02579 Document1-3 Filed06/10/15 Page44 of 64 US 8,398,546 B2 23 24 ment, right or left handedness, body frame size, smoker/ caloric content of the food and the nutrient information is nonsmoker, physical activity level, bed time and wake time. stored in the database. Equivalent foods can be found in the On the reminders screen 1010 the user may select a time zone case of simple preparations. If the user elects to not provide from a pull-down menu in addition to setting a reminder. If detailed nutritional information, a summary meal entry, such any information on the body parameter screen 1005 or the 5 as large, medium or small meal, may be substituted. This will reminders screen1010 is modified, an armband update button provide a baseline nutritional input for the energy balance 1015 allows the user to start the upload process for armband features described herein. Over time, as described more fully configuration 1020. below, the accuracy of these estimations can be improved through feedback of the system which monitors and estimates On the weight goals screen 1025, the user is given the option of setting weight loss goals. If the user selects this 10 the amount of calories actually consumed and correlates the same to the large, medium and small categories. option, the user will be asked to enter the following informa­ tion to establish these goals: current weight, goal weight, goal For greater accuracy, the capability to add custom prepa­ date to reach the goal weight, the target daily caloric intake rations is an option. There are two ways a user can add a and the target daily caloric bum rate. The system will then custom food. The first is by creating a custom food or meal by calculate the following: body mass index at the user's current 15 adding either the ingredients or dishes of a larger composite weight, the body mass index at the goal weight, weight loss dish or meal. The second way is by entering the data found on per week required to reach goal weight by the target date, and the back of processed or packaged foods. Either way constithe daily caloric balance at the entered daily intake and burn tutes an addition to the user's food database for later retrieval, rates. The screen may also display risk factor bars that show If the user wants to add their own custom food, the food the risk of certain conditions such as diabetes, heart disease, 20 database provides the capability to the user to name their own hypertension, stroke and premature death at the user's current preparation, enter the ingredients and also the caloric and weight in comparison to the risk at the goal weight. The nutrient contents. When entering a custom preparation, the current and goal risk factors of each disease state may be user must specify a name and at leastone ingredient. Oncethe displayed side-by-side for the user. The user is given a start preparation is added as a custom food to the database, it is over option 1030 if they have not entered any information for 25 available to be selected as the rest of the foods in the database more than 5 days. for that user. The custom food data may include calories, total The user may also establish a diet and exercise plan on the fat, sodium content, total carbohydrate content, total protein diet and exercise plan screen 1035 from a selection of plans content, fiber and cholesterol in each serving. These values which may includea low carb, high protein diet plan or a more may be estimated based on the ingredients entered. health condition related diet and exercise plan such as that 30 Another aspect of the current invention is to utilize adap­ prescribed by the American Heart Association or the Ameri­ tive and inferential methods to further simplify the food entry can Diabetes Association. It is to be specifically noted that all process. These methods include helping the user correctly such diets, including many not listed herein, are interchange­ choose the portion sizes of meals or ingredients and by autoable for the purposes of this application. The user's diet plan matically simplifying the system for the user over time. One is selected from a pull-down menu. The user also enters their 35 example of the first method is to query the user when certain expected intake of fat, carbohydrates and protein as percentfoods are entered. For example, when lasagna is entered, the ages of their overall caloric intake. The user also selects user is queried about details of thelasagna dish to help narrow appropriate exercises from a pull down menu or these exerdown the caloric content of the food. Furthermore, the user's portion sizes can be compared to the typical portion sizes cises can be manually entered. According to one aspect of the present invention, the sys- 40 entered for the given meal, and the user is queried when their tem generates individualized daily meal plans to help the user entry is out of range. Finally, the user can be queried about attain their health and fitness goals. The system uses a datacommonly related foods when certain foods are entered. For base of foodand meals (combinations of foods) to create daily example, when a turkey sandwich is entered, the user can be menus. The database of food and meals is used in conjunction prompted about condiments, since it is highly likely that some with user preferences, health and fitness goals, lifestyle, body 45 condiments were consumed. In general, these suggestions are type and dietary restrictions which constrain the types of driven based on conditional probabilities. Given that the user meals included in the menu. These individual constraints had beer, for example, the system might suggest pizza. These determine a personalized calorie range and nutritional breaksuggestions can be hard-coded or derived from picking out down forthe user's meal plan. Meals areassigned to menus in common patterns in the population database or a regional, a best-first strategy to fall within a desired tolerance of the 50 familial, seasonal or individual subset, optimal daily caloric and nutritional balance. In a similar vein, the user's patterns and their relationship According to another aspect of the present invention, the to the rest of the population can also be used to drive other system may utilize the information regarding the user's daily aspects of the food entry interaction. For example, if the user energy expenditure to produce menus with calories that may has a particular combination of foods regularly, the system compensate for the user's actual eneigy expenditure through- 55 suggests that the user make that combination a custom meal. out the day. For example, if a user typically exercises right Another aspect of this invention is that the order of foods in before lunch, the lunch can be made slightly larger. The the frequent food list or in the database lookup can be feedback between the information gathered from the arm­ designed to maximize the probability that the user will select band and the menus can help the user achieve fitness and foods with the fewest clicks possible. Instead of launching the health goals more quickly. 60 page with a blank meal, the system can also guess at the meal The user logs meals on a daily basis by selecting individual using the historical meal entry information, the physiological data, the user's body parameters, general population food food items from the food database. The food database pro­ vides an extensive list of commonly consumed foods, e.g., entry data, or in light of relationships with specific other milk, bread, common foods available at certain regional or users. For example, if the system has noticed that two or more national restaurant chains, e.g., McDonald's and Bulger 65 users often have nearly identical meals on a regular pattern, King, as well as brand name entrees, e.g., Weight Watchers or the system can use one user's entry to prompt the second user. Mrs. T's, available in grocery stores. The name of the food, For example, if a wife had a cheeseburger, the system can Case3:15-cv-02579 Document1-3 Filed06/10/15 Page45 of 64 US 8,398,546 B2 25 26 prompt the husband with the same meal. For a group of six the user may be directed a second weight discrepancy error individuals that seems to all have a particular brand of sand­ page 10856 displaying a list of potential reasons for the dis­ wiches for lunch on Tuesdays, the system can use the input crepancy. from one to drive the promptings for the other users. Addi­ Another aspect of the weight tracking subsystem is the tionally, in institutional settings, such as a hospital or lo 5 estimation of the date at which the user's weight should equal assisted living center, where large numbers of the same meal the defined goal value input by the user during the registration or meals are being distributed, a single entry for each meal or as updated at a later time. An algorithm calculates a rate of component could be utilized for all of the wearer/patients. weight change based on the sequence of the user's recorded weight entries. A Kalman smoother is applied to the sequence Another aspect is to use the physiology directly to drive 10 to eliminate the effects of noise due to scale imprecision and suggestions, for example, if the system detects a large amount day to day weight variability. The date at which the user will of activity, sports drinks can be prompted. reach their weight goal is predicted based on the rate of The food input screen is the front end to the food database. weight change. The user interface provides the capability to search the food The total energy expenditure of the user can be estimated database. The search is both interactive and capable of letter 15 either by using the apparatus or by manually entering the and phrase matching to speed input. The user begins a search duration and type of activities. The apparatus automates the by entering at least three characters in the input box. The estimation process to speed up and simplify data entry, but it search should be case insensitive andorder independent of the is not required for the use of the system. It is known that total words entered into the input box. The results of the food search may be grouped in categories such as My Foods, 20 body metabolism is measured as total energy expenditure (TEE) according to the following equation: Popular Foods or Miscellaneous Foods. Within each group in the search results, the foods should be listed first with foods TEE=BMR+AE+TEF+AT, that start with the search string and then alphabetically. After wherein BMR is basal metabolic rate, which is the energy selecting a food item, the user selects the portion size of the selected food. The portion size and the measure depend upon 25 expended by the body during rest such as sleep; AE is activity energy expenditure, which is the eneigy expended during the food selected, e.g., item, serving, gram, ounce. Meal physical activity; TEF is thermic effect of food, which is the information canalso be edited after it is entered. The user may energy expended while digesting and processing the food that enter as many different meals per day as they choose includ­ is eaten; and AT is adaptive thermogenesis, which is a mechaing breakfast, after breakfast snack, lunch, after lunch snack, dinner and after dinner snack. The system may also automati- 30 nism by which the body modifies its metabolism to extreme temperatures. It is estimated that it costs humans about 10% cally populate the user's database of custom foods with the of the value of food that is eaten to process the food. TEF is entries from their selected meal plan. This will provide a simple method for the user to track what they have consumed therefore estimated to be 10% of the total calories consumed. Thus, a reliable and practical method of measuring TEF and also a self reported way of tracking compliance with the program. 35 would enable caloric consumption to be measured without FIG. 8 is a block diagram illustrating a weight tracking the need to manually track or record food related information. subsystem 1040 which allows a user to record weight changes Specifically, once TEF is measured, caloric consumption can over time and receive feedback.A userenters an initial weight be accurately estimated by dividing TEF by 0.1 (TEF=0.1*Calories Consumed; Calories Consumed=TEF/ entry 1045 into the weight tracking subsystem 1040. The weight tracking subsystem 1040 calculates the percent 40 0.1). FIG.9isablock diagram of the update information wizard weight change 1050 since the last time the user has made a interface 1090 illustrating the process of data retrieval from weight entry. If a newly entered weight is more than 3% above the apparatus to update eneigy expenditure. The user is given or below the last weight, a weight verification page 1055 is displayed for the user to confirm that the entered weight is at least three options for updating energy expenditure includcorrect. If the entered weight is not more than 3% above or 45 ing: an unable to upload armband data option 1095a, a forgot to wear armband data option 10956, and an upload armband below the last weight, the weight tracking subsystem 1040 data option 1095c. saves the entry as the current weight 1060. It is to be specifi­ When data is retrieved from the apparatus, the system may cally noted that the weight tracking subsystem 1040 may provide a semi-automated interface. The system is provided utilize body fat measurements and calculations in addition to, 50 with the capability to communicate with the apparatus both or in substitution for, the weight entry 1045. The current weight 1060 is compared to the target weight wirelessly and with a wired USB connection. The system selected by the user through a weight loss comparison 1065. prompts the user to select the mode of communication before If a weight is entered which is equal to or below the goal the retrieval of data. It is contemplated that the most common weight, a congratulatory page 1070 displays which has fields usage model may be wireless retrieval. If wireless retrieval is for resetting the goal weight. In the preferred embodiment, a 55 used, a wired connection could be used primarily for field comparison is made every six entries between the current upgrades of the firmware in the armband. Each apparatus is weight x and the (x-6)"! weight to determine an interval associated with a particular user and the apparatus is person­ weight loss 1075. Based on the information provided by the alized so that it cannot be interchanged between different users. user in the registration process regarding weight loss goals, in addition to the input of the user through use of the system, an 60 The system will use the data collected by the armband for expected weight loss1080 is calculated based on these nutri­ estimating the total energy expenditure. This value is calcu­ tional and energy expenditure values. If interval weight loss lated using an algorithm contained within the software. The 1075 between the two weights is greater than 10 or more database stores the minute-by-minute estimates of the energy pounds from the preprogrammed expected weight loss 1080, expenditure values, the number of steps, the amount of time the user may be directed to a weight discrepancy error page 65 the apparatus was worn, the active energy expenditure values, 1085a directing the user to contact technical support. If the the user's habits, which, in the preferred embodiment are difference between the two weights if four pounds or more, stored as typical hourly non-physically active eneigy expen- Case3:15-cv-02579 Document1-3 Filed06/10/15 Page46 of 64 US 8,398,546 B2 27 28 diture, their reported exercise while not wearing the appara­ tus, and the time spent actively. Referring again to FIG. 9, if the user selects the unable to upload armband data option 1095a or the forgot to wear armband option10956, the user may elect the estimate energy expenditure option 1100, If the user selects the upload arm­ band data option 1095c, the user may begin retrieving the data from the apparatus. If the apparatus was worn intermittently or not worn for a period of time, the system can provide the user with a manual activity entry option 1105 to manually enter the type of activity they have engaged in during this period. The options available include a sedentary option, a list of activities from the American College of Sports Medicine Metabolic Equivalent Table and a list of activities previously entered during the use of the device. Over time, the options may be presented in order of highest to lowest incidence, speeding the data input by placing the most frequent options at the top of the list. Additionally, the system may observe patterns of activity based upon time of day, day of the week and the like and suggest an activity with high probability for the particular missing time period. If nothing was entered for activities, the system will estimate the user's energy expen­ diture using their previously stored data. In the preferred embodiment, this is done using a histogram estimation and analysis incorporating a set of hourly data sets, each of which includes a running average of the non-exercise energy expen­ diture recorded by the apparatus. Additionally, the user may select a exercise calculator to estimate the calories burned during any particular activity in the database. The user selects the appropriate activity from a list and a time period for the activity. The system calculates the approximate calories that would be burned by the user during that time period, based upon either or both of (i) a lookup table of average estimate data or (ii) prior measure­ ments for that user during those specific activities. According to an aspect of the present invention, the arm­ band may detect when the user is physically active and sed­ entary. During the physically active times, the usage patterns are not updated. Instead the user is asked to report on their highly active periods. During the non-physically active times, the usage pattern is updated and the information gathered is then used during reported sedentary time when the user did not wear the armband. The system, either through the software platform, the body monitor, or both, can improve its performance in making accurate statements about the wearer by gathering and ana­ lyzing data, finding patterns, finding relations, or correlating data about the person overtime. Forexample, if the user gives explicit feedback, such as time stamping a particular activity to the system, the system can this to directly improve the system's ability to identify that activity. As another example, the system can build a characterization of an individual's habits over time to further improve the quality of the derived measures. For example, knowing the times a user tends to exercise, for how long they tend to exercise, or the days they tend not to exercise can all be valuable inputs to the prediction of when physical activity is occurring. It will be obvious to one skilled in the art that the characterizations of habits and detected patterns are themselves possible derived parameters. Furthermore, these characterizations of habits and patterns can allow the system to be intuitive when the sensors are not working or the apparatus is not attached to the user's body. For example, if the user does not wear the apparatus and measured energy expenditure is not available, or neglects to input a meal, the data can be estimated from the characterizations of habits and prior observed meals and activities, as stated more fully herein. For the more general embodiment, the Activity Level cat­ egory of Health Index 155 is designed to help users monitor how and when they move around during the day and utilizes both data input by the user and data sensed by sensor device 10. The data input by the user may include details regarding the user's daily activities, for example the fact that the user worked at a desk from 8 a.m. to 5 p.m. and then took an aerobics class from 6 p.m. to 7 p.m. Relevant data sensed by sensor device 10 may include heart rate, movement as sensed by a device such as an accelerometer, heat flow, respiration rate, calories burned, GSR and hydration level, which may be derived by sensor device 60 or central monitoring unit 30. Calories burned may be calculated in a variety of manners, including: the multiplication of the type of exercise input by the user by the duration of exercise input by the user; sensed motion multiplied by time of motion multiplied by a filter or constant; or sensed heat flux multiplied by time multiplied by a filter or constant. The Activity Level Health Index piston level is preferably determined with respect to a suggested healthy daily routine that includes: exercising aerobically for a pre-set time period, preferably 20 minutes, or engaging in a vigorous lifestyle activity for a pre-set time period, preferably one hour, and burning at least a minimum target number of calories, preferably 205 calories, through the aerobic exercise and/or lifestyle activity. The minimum target number of calories may be set according to information about the user, such as sex, age, height and/or weight. Parameters utilized in the calcula­ tion of the relevant piston level include the amount of time spent exercising aerobically or engaging in a vigorous lifestyle activity as input by the user and/or sensed by sensor device 10, and the number of calories burned above precalculated energy expenditure parameters. Information regarding the individual user's movement is presented to the user through activity level web page 200 shown in FIG. 10, whichmay includeactivity graph 205 inthe form of a bar graph, for monitoring the individual user's activities in one of three categories: high, medium and low intensity with respect to a pre-selected unit of time. Activity percentage chart 210, in the form or a pie chart, may also be provided for showing the percentage of a pre-selected time period, such as one day, that the user spent in each category. Activity level web page 200 may also include calorie section 215 for displaying items such as total calories burned, daily target calories burned, total caloric intake, and duration of aerobic activity. Finally, activity level web page 200 may include at least one hyperlink 220 to allow a user to directly access relevant news items and articles, suggestions for refin­ ing or improving daily routine with respect to activity level and affiliate advertising elsewhere on the network. Activity level web page 200 may be viewed in a variety of formats, and may include user-selectable graphs and charts such as a bar graph, pie chart, or both, as selectable by Activity level check boxes 225. Activity level calendar 230 is provided for selecting among views having variable and selectable time periods. The items shown at 220 may be selected and customized based on information learned about the individual in the survey and on their performance as measured by the Health Index. The Mind Centering category of Health Index 155 is designed to help users monitor the parameters relating to time spent engaging in certain activities which allow the body to achieve a state of profound relaxation while the mind becomes focused, and is based upon both data input by the user and data sensed by the sensor device 10. In particular, a user may input the beginning and end times of relaxation activities such as yoga or meditation. The quality of those 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page47 of 64 US 8,398,546 B2 29 30 activities as determined by the depth of a mind centering event can be measured by monitoring parameters including skin temperature, heart rate, respiration rate, and heat flow as sensed by sensor device10. Percent change in GSR as derived either by sensor device 10 or central monitoring unit 30 may also be utilized. The Mind Centering Health Index piston level is preferably calculated with respect to a suggested healthy daily routine that includes participating each day in an activity that allows the body to achieve profound relaxation while the mind stays highly focused for at least fifteen minutes. Parameters utilized in the calculation of the relevant piston level include the amount of time spent in a mind centering activity, and the percent change in skin temperature, heart rate, respiration rate, heat flow or GSR as sensed by sensor device 10 com­ pared to a baseline which is an indication of the depth or quality of the mind centering activity. Information regarding the time spent on self-reflection and relaxation is presented to the user through mind centering web page 250 shown in FIG. 11. For each mind centering activity, referred to as a session, the preferred mind centering web page 250 includes the time spent during the session, shown at 255, the target time, shown at 260, comparison section 265 showing target and actual depth of mind centering, or focus, and a histogram 270 that shows the overall level of stress derived from such things as skin temperature, heart rate, respiration rate, heat flow and/or GSR. In comparison section 265, the human figure outline showing target focus is solid, and the human figure outline showing actual focus ranges from fuzzy to solid depending on the level of focus. The preferred mind centering web page may also include an indication of the total time spent on mind centering activities, shown at 275, hyperlinks 280 which allow the user to directly access relevant news items and articles, suggestions for refin­ ing or improving daily routine with respect to mind centering and affiliate advertising, and a calendar 285 for choosing among views having variable and selectable time periods. The items shown at 280 may be selected and customized based on information learned about the individual in the survey and on their performance as measured by the Health Index. The Sleep category of Health Index 155 is designed to help users monitor their sleep patterns and the quality of their sleep. It is intended to help users learn about the importance of sleep in their healthy lifestyle and the relationship of sleep to circadian rhythms, being the normal daily variations in body functions. The Sleep category is based upon both data input by the user and data sensed by sensor device 10. The data input by the user for each relevant time interval includes the times the user went to sleep and woke up and a rating of the quality of sleep. As noted in Table 2, the data from sensor device 10 that is relevant includes skin temperature, heat flow, beat-to-beat heart variability, heart rate, pulse rate, respiration rate, core temperature, galvanic skin response, EMG, LEG, LOG, blood pressure, and oxygen consumption. Also rel­ evant is ambient sound and body movement or motion as detected by a device such as an accelerometer. This data can then be used to calculate or derive sleep onset and wake time, sleep interruptions, and the quality and depth of sleep. The Sleep Health Index piston level is determined with respect to a healthy daily routine including getting a mini­ mum amount, preferably eight hours, of sleep each night and having a predictable bed time and wake time. The specific parameters which determine the piston level calculation include the number of hours of sleep per night and the bed time and wake time as sensed by sensor device 10 or as input by the user, and the quality of the sleep as rated by the user or derived from other data. Information regarding sleep is presented to the user through sleep web page 290 shown in FIG. 12. Sleep web page 290 includes a sleep duration indicator 295, based on either data from sensor device 10 or on data input by the user, together with user sleep time indicator 300 and wake time indicator 305. A quality of sleep rating 310 input by the user may also be utilized and displayed. If more than a one day time interval is being displayed on sleep web page 290, then sleep duration indicator 295 is calculated and displayed as a cumulative value, and sleep time indicator 300, wake time indicator 305 and quality of sleep rating 310 are calculated and illustrated as averages. Sleep web page 290 also includes a user-selectable sleep graph 315 which calculates and dis­ plays one sleep related parameter over a pre-selected time interval. For illustrative purposes, FIG. 12 shows heat flow over a one-day period, which tends to be lower during sleeping hours and higher during waking hours. From this informnation, a person's bio-rhythms can be derived. Sleep graph 315 may also include a graphical representation of data from an accelerometer incorporated in sensor device 10 which monitors the movement of the body. The sleep web page 290 may also include hyperlinks 320 which allow the user to directly access sleep related news items and articles, sugges­ tions for refining or improving daily routine with respect to sleep and affiliate advertising available elsewhere on the net­ work, and a sleep calendar 325 for choosing a relevant time interval. The items shown at 320 may be selected and cus­ tomized based on information learned about the individual in the survey and on their performance as measured by the Health Index. The Activities of Daily Living category of Health Index 155 is designed to help users monitor certain health and safety related activities and risks and is based in part on data input by the user. Other data which is utilized by the Activities of Daily Living category is derived from the sensor data, in the form of detected activities which are recognized based on physiological and/or contextual data, as described more fully in this application. The Activities of Daily Living category is divided into four sub-categories: personal hygiene, which allows the user to monitor activities such as brushing and flossing his or her teeth and showering; health maintenance, that tracks whether the user is taking prescribed medication or supplements and allows the user to monitor tobacco and alcohol consumption and automobile safety such as seat belt use; personal time, that allows the user to monitor time spent socially with family and friends, leisure, and mind centering activities; and responsibilities, that allows the user to monitor certain work and financial activities such as paying bills and household chores. The Activities of Daily Living Health Index piston level is preferably determined with respect to the healthy daily routine described below. With respect to personal hygiene, the routine requires that the users shower or bathe each day, brush and floss teeth each day, and maintain regular bowel habits. With respect to health maintenance, the routine requires that the user take medications and vitamins and/or supplements, use a seat belt, refrain from smoking, drink moderately, and monitor health each day with the Health Manager. With respect to personal time, the routine requires the users to spend at least one hour of quality time each day with family and/or friends, restrict work time to a maximum of nine hours a day, spend some time on a leisure or play activity each day, and engage in a mind stimulating activity. With respect to responsibilities, the routine requires the users to do household 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page48 of 64 US 8,398,546 B2 31 32 chores, pay bills, be on time forwork, and keep appointments. The piston level is calculated based on the degree to which the user completes a list of daily activities as determined by information input by the user. Information relating to these activities is presented to the user through daily activities web page 330 shown in FIG. 13. In preferred daily activities web page 330, activities chart 335, selectable for one or more of the sub-categories, shows whether the user has done what is required by the daily routine. A colored or shaded box indicates that the user has done the required activity, and an empty, non-colored or shaded box indicates that the user has not done the activity. Activities chart 335 can be created and viewed in selectable time intervals. For illustrative purposes, FIG. 13 shows the personal hygiene and personal time sub-categories for a particular week. In addition, daily activities web page 330 may include daily activity hyperlinks 340 which allow the user to directly access relevant news items and articles, suggestions for improving or refining daily routine with respect to activi­ ties of daily living and affiliate advertising, and a daily activities calendar 345 for selecting a relevant time interval. The items shown at 340 may be selected and customized based on information learned about the individual in the survey and on their performance as measured by the Health Index. The How You Feel category of Health Index 155 is designed to allow users to monitor their perception of how they felt on a particular day, and is based on information, essentially a subjective rating, that is input directly by the user. A user provides a rating, preferably on a scale of 1 to 5, with respect to thefollowing nine subject areas: mental sharpness; emotional and psychological well being; energy level; ability to cope with life stresses; appearance; physical well being; self-control; motivation; and comfort in relating to others. Those ratings are averaged and used to calculate the relevant piston level. Referring to FIG. 14, Health Index web page 350 is shown. Health Index web page 350 enables users to view the perfor­ mance of their Health Index over a user selectable time interval including any number of consecutive or non-consecutive days. Using Health Index selector buttons 360, the user can select to view the Health Index piston levels for one category, or can view a side-by-side comparison of the Health Index piston levels for two or more categories. For example, a user might want to just turn on Sleep to see if their overall sleep rating improved over the previous month, much in the same way they view the performance of their favorite stock. Alter­ natively, Sleep and Activity Level might be simultaneously displayed in order to compare and evaluate Sleep ratings with corresponding Activity Level ratings to determine if any dayto-day correlations exist. Nutrition ratings might be displayed with How You Feel for a pre-selected time interval to deter­ mine if any correlation exists between daily eating habits and how they felt during that interval. For illustrative purposes, FIG. 14 illustrates a comparison of Sleep and Activity Level pistonlevels for the week of June lOthrough June 16. Health Index web page 350 also includes tracking calculator 365 that displays access information and statistics such as the total number of days the user has logged in and used the Health Manager, the percentage of days the user has used the Health Manager since becoming a subscriber, andpercentage of time the user has used the sensor device 10 to gather data. Referring again to FIG. 5, opening Health Manager web page 150 may include a plurality of user selectable category summaries 156a through 156/ one corresponding to each of the Health Index 155 categories. Each category summary 156a through 156f presents a pre-selected filtered subset of the data associated with the corresponding category. Nutri- tion category summary 156a displays daily target and actual caloric intake. Activity Level category summary 156b dis­ plays daily taiget and actual calories burned. Mind Centering category summary 156c displays target and actual depth of mind centering or focus. Sleep category summary 156d dis­ plays target sleep, actual sleep, and a sleep quality rating. Daily Activities category summary 156e displays a target and actual score based on the percentage of suggested daily activi­ ties that are completed. The How You Feel category summary 156/shows a target and actual rating for the day. Opening Health Manager web page 150 also may include Daily Dose section157 which provides, on a daily time inter­ val basis, information to the user, including, but not limited to, hyperlinks to news items and articles, commentary and reminders to the user based on tendencies, such as poor nutritional habits, determined from the initial survey. The com­ mentary for Daily Dose 157 may, for example, be a factual statement that drinking 8 glasses of water a day can reducethe risk of colon cancer by as much as 32%, accompanied by a suggestion to keep a cup of water by your computer or on your desk at work and refill often. Opening Health Manager web page 150 also may include a Problem Solver section 158 that actively evaluates the user's performance in each of the cat­ egories of Health Index 155 and presents suggestions for improvement. For example, if the system detects that a user's Sleep levels have been low, which suggest that the user has been having trouble sleeping, Problem Solver 158 can pro­ vide suggestions for way to improve sleep. Problem Solver 158 also may include the capability of user questions regarding improvements in performance. Opening Health Manager web page 150 may also include a Daily Data section 159 that launches an input dialog box. The input dialog box facilitates input by the user of the various data required by the Health Manager. As is known in the art, data entry may be in the form of selection from pre-defined lists or general free form text input. Finally, opening Health Manager web page 150 may include Body Stats section 161 which may provide informa­ tion regarding the user's height, weight, body measurements, body mass index or BMI, and vital signs such as heart rate, blood pressure or any of the identified physiological parameters. Referring again to the weight management embodiment, energy balance is utilized to track and predict weight loss and progress. The energy balance equation has two components, energy intake and energy expenditure, and the difference between these two values is the energy balance. Daily caloric intake equals the number of calories that a user consumes within a day. Total energy expenditure is the amount of calo­ ries expended by a user whether at rest or engaging in any type of activity. The goal of the system is to provide a way to track daily caloric intake and automatically monitor total energy expenditure accurately so users can track their status and progress with respect to these two parameters. The user is also provided with feedback regarding additional activities necessary to achieve their eneigy balance. To achieve weight loss the energy balance should be negative which means that fewer calories were consumed than expended. A positive energy balance has the potential to result in weight gain or no loss of weight. The management system automates the ability of the user to track eneigy balance through the energy intake tracking subsystem, the eneigy expenditure tracking sub­ system and the eneigy balance and feedback subsystem. Referring again to FIG. 9, if the user has not entered any meals or food items consumed since the last update, the user will be prompted to initiate the energy intake subsystem1110 to log caloric intake for the appropriate meals. The energy intake subsystem may estimate the average daily caloric 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page49 of 64 US 8,398,546 B2 33 34 intake of the user using the total energy expenditure estimate and the change in the user's weight and/or body fat compo­ sition. The inputs to this system include the user's body fat composition or weight, at regular intervals related to the relevant time period, and the energy expenditure estimation. If the user has not updated their weight within the last 7 days, they will be directed to a weight reminder page 1115. The energy expenditure estimation is based on the basic equiva­ lence of 3500 kcal equal to a 1 lb change in weight. The software program will also attempt to smooth the estimation by accounting for fluctuations in water retained by the body and for differences in the way the user has collected weight readings, e.g. different times of the day or different weight scales. It is to be specifically noted that the system may also be utilized to derive the caloric intake from the energy expendi­ ture of the user and the changes in weight which are input by the user or otherwise detected by the system. This is accom­ plished by utilizing the same basic calculations described herein, however the net weight gain or loss is utilized as the reference input. In the equation A+B=C, A is equal to caloric intake, B equal to eneigy expenditure and C equal to the net weight gain or loss. The system may not be able to determine the specific information regarding the type of food items consumed by the user, but it can calculate what the caloric intake for the user would be, given the known physiological parameters and the energy expenditure measured during the relevant time period. Changes in body fat and water weight may also be incorporated into this calculation for greater accuracy. This calculation of daily caloric intake may also be per­ formed even when the user is entering nutritional information as a check against the accuracy of the data input, or to tune the correlation between the small, medium and large size meal options described above, in the more simplified method of caloric input, and the actual calorie consumption of the user, as is disclosed in co-pending U.S. patent application Ser. No. 10/682,759, the specification of which is incorporated herein by reference. Lastly, this reverse calculation can be utilized in the institutional setting to determine whether or to what degree the patients are consuming the meals provided and entered into the system. Logging of the foods consumed is completely optional for the user. By using this feature the user can get feedback about how much food they think they consumed compared to what they actually consumed, as measured by the energy intake estimation subsystem described above. If the user chooses to log food intake, a semi automated interface guides the user through the breakfast, after breakfast snack, lunch, after lunch snack, dinner, and after dinner snack progression. If the user does not have the need to enter any data, e.g., the user did not have a snack after breakfast, options may be provided to skip the entry. Immediate feedback about the caloric content of the selected foods also may be provided. For any of the 6 meal events, the software assumes one of the following scenarios to be true: a user has eaten the meal and wants to log in what they ate food by food; a user has eaten the meal but has eaten the same thing as a previous day; a user has eaten the meal but can not recall what they ate; a user has eaten the meal, can recall what they ate, but does not want to enter in what they ate food by food; a user has skipped the meal; a user has not eaten the meal yet. The software forces the user to apply these scenarios for each meal chro­ nologically since the last meal event was entered into the system. This ensures there are no gaps in the data. Gaps in the data lead to misleading calculations of calorie balance. If the user wants to log food items, the software responds by prompting the user to type in the first few letters of a food into the dynamic search box which automatically pulls the closest matches from the food database into a scrollable drop down list just below the entry. Upon selection of an entry, the food appears in a consumed foods list to the right of the drop down, where addition of information such as unit of measure and serving size can be edited, or the food can be deleted from the consumed foods list. The total number of calories per meal is automatically calculated at the bottom of the consumed foods list. This method is repeated until the meal has been recounted. In the event that a food does not exist in the database, a message appears in the drop down box suggesting that the user can add a custom food to their personal database. If a user has eaten the same thing as a previous day, the user selects the appropriate day and the meal chosen appears to the right. The user hits the next button to enter it into the system. This specifically capitalizes on the tendency of people to have repetitive eating patterns such as the same foods for the same meals over increments of time. If a user cannot recall a meal, the software responds by bringing up a screen that calculates an average of the total number of calories consumed for that meal over a certain number of days and presents that number to the user. If the user has eaten a meal, but does not want to enter the consumed food items, the software may bring up a screen that enables the user to quickly estimate caloric intake by either entering a number of calories consumed or selecting a word amount such as normal, less than normal, more than normal, a lot or very little. Depending on the selection, estimated caloric intake increases or decreases from the average, or what is typical based on an average range. For example, if on average the user consumes between 850 and 1000 kcal for dinner, and specifies that for the relevant meal that heate more than usual, the estimate may be higher than 1000 kcal. If a user specifies that they did not eat a certain meal yet, they may choose to proceed to theweight management center. This accounts for the fact that users eat meals at different points of the day, but never one before the other. To keep the amount of time a user has to spend entering the meal information to a minimum, the system may also offerthe option to select from a list of frequently consumed foods. The user can select food items from the frequent foods list and minimize the need to search the database for commonly consumed foods. The frequent foods tool is designed to further expedite the task of accurately recalling and entering food consumption. It is based on the observation that people tend to eat only 35-50 unique foods seasonally. People tend to eat a core set of favorite breakfast foods, snacks, side dishes, lunches, and fast food based on personal preference, and issues concerning convenience, like places they can walk or drive to from work for lunch. The frequent foods tool works by tallying the number of times specific food entries are selected from the database by the user for each of the six daily meal events. The total number of selections of a specific food entry is recorded, and the top foods with the most selections appears in a frequent foods list in order of popularity. Addi­ tionally, the system is also aware of other meal related param­ eters of the user, such as meal plan or diet type, and speeds data entry by limiting choices or placing more relevant foods at the top of the lists. FIG. 15 is a representation of a preferred embodiment of the Weight Manager interface 1120. Weight Manager inter­ face 1120 is provided with a multi section screen having a navigation bar 1121 which comprises a series of subject mattertabs 1122. The tabs are customizable with the program but typically include sections for report writing and selection 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page50 of 64 US 8,398,546 B2 35 36 1122b, a navigation tab to the user's profile 1122c, a naviga­ tion tab to the armband sensor device update section 1122d, a Another aspect of this alternative embodiment of the feed­ back system is that the system can evaluate the results of giving the feedback to the user. This is accomplished through the tracking of the parameters which are the subject of the feedback, such as context and estimated daily caloric intake or logged intake. This feature enables the system to be obser­ vational and not just result based, because it can monitor the nature of compliance and modify the feedback accordingly. For example, if the system suggests eating less, the system can measure how much less the user eats in the next week and use this successful response as feedback to tune the system's effectiveness with respect to the user's compliance with the original feedback or suggestions. Other examples of such delayed feedback for the system are whetherthe user exercises more when the system suggests it, whether the user undertakes more cardiovascular exercise when prompted to, and whether the user wears the armband more when it is suggested. This type of delayed feedback signal, and the system's subsequent adaptation thereto is identified as reinforcement learning, as is well known in the art. This learning system tunes the behavior of a system or agent based on delayed feedback signals. In this alternate embodiment, the system is tuned at three levels of specificity through the reinforcement learning framework. First, the feedback is adapted for the entire population for a given situation, e.g. what is the right feedback to give when the user is in a plateau. Second, the feedback is adapted for groups of people, e.g. what is the right feedback in situation X for people like person Y or what is the right feedback for women when the person hasn't been achieving intake goals for three weeks, which may be different from the nature or character or tone of the feedback given to men under the same conditions. Finally, the system can also adapt itself directly based on the individual, e.g. i.e., what is the best feedback for this particular user who has not exercised enough in a given week. In another aspect of the invention, the feedback provided to the user might be predictive in nature. At times, an individual may experience non-goal or negatively oriented situations, such as weight gain, during a weight loss regimen. The situations may also be positive or neutral. Because of the con­ tinuous monitoring of data through the use of the system, the events surrounding, that is, immediately prior and subsequent to, the situation can be analyzed to determine and classify the type of event. The sequence of events, readings or parameters can be recorded as a pattern, which the system can store and review. The system can compare current data regarding this situation to prior data or patterns to determine if a similar situation has occurred previously and further to predict if a past episode is going to occur in the near term. The system may then provide feedback regarding the situation, and, with each occurrence, the system can tailor the feedback provided to the user, based on the responses provided by or detected from the user. The system can further tailor the feedback based on the effectiveness of the feedback. As the system is further customized for the user, the system may also proactively make suggestions based on the user's detected responses to the feedback. For example, in the situation where a user has reached a plateau in weight management, the system may formulate new suggestions to enable a user to return to a state of progress. Furthermore, the system modifies the reinforcement learn­ ing framework with regard to detected or nondetected responses to the provided feedback. For example, if the system suggests that the user should increase their energy expenditure, but the individual responds by wearing the armband more often, the system can modify the framework based on navigation tab to the meal entry section 11226 and a message section 1122/ The interface 1120 is further provided, as shown in FIG. 15, with an operational section 1122a entitled balance which comprises the primary user functions of the Weight Manager interface 1120. A calendar section 1123 provides the user with the ability to select and view data from or for any particular date. A feedback section 1125 provide commentary as described herein, and a dashboard section 1126 provides graphical output regarding the selected days energy intake and expenditure. Finally, a weight loss progress section 1135 provides a graphical output of weight versus time for any given date selected in calendar section 1123. A feedback and coaching engine analyzes the data generated by the total energy expenditure and daily caloric intake calculations, as previously discussed, to provide the user with feedback in the feedback section 1125. The feedback may present a variety of choices depending on the current state of the progress of the user. If the user is both losing weight and achieving the target daily caloric intake and total energy expenditure goals, they are encouraged to continue the pro­ gram without making any adjustments. If the user is not losing weight according to the preset goals, the user may be presented with an option to increase the total energy expenditure, decrease the daily caloric intake, combination of increase in total energy expenditure and decrease in daily caloric intake to reach energy balance goals or reset goals to be more achievable. The feedback may further include sug­ gestions as to meal and vitamin supplements. This feedback and coaching may also be incorporated in the intermittent status reports described below, as both present similar infor­ mation. If the user chooses to decrease daily caloric intake the user may be presented with an option to generate a new meal plan to suit their new daily caloric goal. If the user chooses to increase total expenditure energy goal, the user may be pre­ sented with an exercise plan to guide them to the preset goals. A total eneigy expenditure estimation calculator utility may also be available to the users. The calculator utility may enable the user to select from multiple exercise options. If the user chooses to increase total energy expenditure and decrease daily caloric intake to reach the preset goals, the meal plan and exercise choices may be adjusted accordingly. Safety limitations may be placed on both the daily caloric intake and total energy expenditure recommendations. For example, a meal plan with fewer than 1200 kcal a day and exercise recommendations for more than an hour a day may not be recommended based on theimposed safety limitations. Additionally, the user may be provided with suggestions for achieving a preset goal. These suggestions may include simple hints, such as to wear their armband more often, visit the gym more, park farther from the office, or log food items more regularly, as well as specific hints about why the user might not be seeing the expected results. In an alternative embodiment, the recommendations given by the coaching engine are based on a wider set of inputs, including the past history of recommendations and the user's physiological data. The feedback engine can optionally engage the user in a serious of questions to elicit the underlying source for their failure to achieve a preset goal. For example, the system can ask questions including whether the user had visitors, was the user out of town over the weekend, was the user too busy to have time to exercise, or if the user dine out a lot during the week. Asking these questions gives the user encouragement and helps the user understand the reasons that a preset goal has not been achieved. 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page51 of 64 US 8,398,546 B2 37 38 the user's sensitivities to the feedback. The reinforcement is not only from the direct interaction of the user with the sys­ tem, but also any difference in behavior, even if the connec­ tion is not immediately obvious. It should be specifically noted that the predictive analysis of the data regarding negatively positively or neutrally ori­ ented situations may be based on the user's personal history or patterns or based on aggregate data of similar data from other users in the population. The population data may be based on the data gathered from users of any of the embodiments of the system, including but not limited to weight management. Moreover, as the user experiences multiple occasions of similar situations, the system may begin to understand how the individual arrived at this stage and how the person attempted to correct the situation, successfully or unsuccess­ fully. The system reinforces its learning and adaptation through pattern matching to further modify future feedback the next time this situation may occur. For example, it is not uncommon in weight management for a user to experience a plateau, which is the slowing of the user's metabolism to slow in order to conserve calories and also a period during which a user may not realize any progress toward preset goals. Also, occasions may occur which cause the user to deviate from a preset goal either temporarily or long-term such as long weekends, vacations, business trips or periods of consistent weather conditions, the system may provide reminders prior to the plateau or the event, warning of an impending problem and providing suggestions for avoidance. In an alternate embodiment, when the user experiences a negative, positive or neutral situation that is likely to affect achieved progress, the system may display the risk factors discussed above as they are affected by the situation. For example, if the user has experienced a negative situation that has caused an increase in weight, the system may determine that the user's risk for heart disease is now elevated. This current elevated risk is displayed accordingly in the risk factor bar for that condition and compared to the risk at the user's goal level. It will be clear to one skilled in the art that the description just given for guiding a person through an automated process of behavior modification with reinforcement with respect to a series of physiologic and/or contextual states of the individu­ al's body and their previous behavior responses, while described for the specific behavior modification goal of weight management, need not be limited to that particular behavior modification goal. The process could also be adapted and applied without limitation to sleep management, pregnancy wellness management, diabetes disease manage­ ment, cardiovascular disease management, fitness management, infant wellness management, and stress management, with the same or other additional inputs or outputs to the system. Equally appreciable is a system inwhich a user is a diabetic using the tool for weight management and, therefore, insulin level and has had a serious or series of symptoms or sudden changes in blood glucose level recorded in the data. In this embodiment, the inputs would be the same as the weight embodiment, calories ingested, types of calories, activity and energy expenditure and weight. With respect to the insulin level, management where the feedback of this system was specifically tuned for predicted body insulin levels, calorie intake, calorie burn, activity classifications and weight measurement could be utilized. User input would include glucometer readings analogous to the weight scale of the weight loss embodiment. It should be noted that insulin level is indirectly related to energy balance and therefore weight management. Even for a non-diabetic, a low insulin level reflects a limita­ tion on energy expenditure, since the body is unable to obtain its maximum potential. In addition to monitoring of physiological and contextual parameters, environmental parameters may also be moni­ tored to determine the effect on the user. These parameters may include ozone, pollen count, and humidity and may be useful for, but not limited to, a system of asthma management. There are many aspects to the feedback that can be adapted in different embodiments of this system. For example, the medium of the feedback can be modified. Based on perfor­ mance, the system can choose to contact the user through phone, email, fax, or the web site. The tone or format of the message itself can be modified, for example by choosing a strong message delivered as a pop-up message. A message such as "You've been too lazy! I'm ordering you to get out there and exercise more this week" or a more softly toned message delivered in the feedback section of the site, such as "You've been doing pretty well,. but if you can find more time to exercise this week, you'll stay closer to your targets", The system may also include a reporting feature to provide a summary of the eneigy expenditure, daily caloric intake, energy balance or nutritional information for a period of time. The user may be provided with an interface to visualize graphically and analyze the numbers of their eneigy balance, The input values for the energy balance calculation are the daily caloric intake that was estimated using the total energy expenditure and weight or body fat changes and total energy expenditure estimates based on the usage of the energy expenditure tracking system. The user may be provided with this information both in an equation form and visually. Short­ cuts are provided for commonly used summary time periods, such as daily, yesterday, last 7 days, last 30 days and since beginning. The report can also be customized in various ways includ­ ing what the user has asked to see in the past or what the user actually has done. The reports may be customized by third party specifications or by user selection. If the user has not exercised, the exercise tab can be left out. The user may ask to see a diary of past feedback to see the type of feedback previously received. If the feedback has all been about con­ trolling daily caloric intake, the reports can be more about nutrition. One skilled in the art will recognize that the reports can be enhanced in all the ways that the feedback engine can be enhanced and can be viewed as an extension of the feedback engine. Referring again to FIG. 15, the balance tab 1122a presents a summary of the user's weight loss progress in a variety of formats. Forthe balance sectionll22a, a weight loss progress graph 1135 illustrates the user's weight loss progress from day the user began using the total weight loss system to the present date. Eneigy balance section 1136 provides details regarding the user's actual and goal energy balance including the actual and goal calories consumed and actual and goal calories burned. Eneigy balance graph 1137 is a graphical representation of this same information. Dashboard section 1126 also has a performance indicator section 1146 which lets the user know the state of their eneigy balance in relation to their goal. The information contained within the performance indicator section 1146 maybe a graphical representati on of the information in the feedback section 1125. Optionally, the system may display a list of the particular foods consumed during the relevant time period and the nutritional aspects of the food, such as calories, carbohydrate and fat content in chart form. Similarly, the display may include a charted list of all activities conducted during the relevant time period together with relevant data such as the duration of the 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page52 of 64 US 8,398,546 B2 39 40 activity and the calories burned. The system may further be The user's current eneigy balance is also used to determine utilized to log such activities at a user-selected level of detail, part of the selection criteria, including individual exercises, calisthenics and the like. In an alternative embodiment, the system may also provide TABLE 4 intermittent feedbackto the user in the feedback section 1125, 5 String Calculation alone or in conjunction with the feedback and coaching engine. The feedback and coaching engine is a more specific (energy expenditure - daily caloric intake) > 40 Black or alternative embodiment of the Problem Solver, as -40 < (energy expenditure - daily caloric intake) < 40 Even 40 < (energy expenditure - daily caloric intake) Red described above. The feedback may also be presented in an additional display box or window, as appropriate, in the form 10 of a periodic or intermittent status report 1140. The intermit­ The last part of the selection criteria depends on the type of tent status report 1140 may also be requested by the user at view selected, as previously described above. Specifically, any time. The status report may be an alert located in a box on the today view incorporates two parameters to predict the a location of the screen and is typically set off to attract the ability of the user to correct the energy balance deficiencies user's attention. Status reports and images are generated by 15 by the end of the relevant time period: creating a key string, or parameter set, based on the user's current view and state and may provide information to the TABLE 5 user about their weight loss goal progress. This information String Description typically includes suggestions to meet the user's calorie bal­ ance goal for the day. 20 Early A favorite activity takes less than an hour Intermittent status reports 1140 are generated on the balto correct the energy balance and it is before 11:00 PM; or an activity appropriate ance tab 1122a of the Weight Manager Interface 1120. The for the user will correct the energy balance purpose of the intermittent status report 1140 is to provide and enough time remains in the relevant period for its completion. immediate instructional feedback to the user for the selected Late A favorite activity takes more than an hour view. A properties file containing key value pairs is searched 25 to correct the energy balance or it is after to match message and images which establishes certain selec­ 11:00 PM; or there is insufficient time to complete an activity which will return a tion criteria to the corresponding key. positive result for energy balance. In the preferred embodiment, there are four possible views for intermittent status reports 1140: Today, Specific Day, All other views use two types of information for estimating Average (Last 7 or 30 Day) and Since Beginning. A user state is incorporated as part of the selection criteria the validity of the goals: for intermittent status report 1140. The user state is based on TABLE 6 the actual and goal values of eneigy expenditure and daily caloric intake as previously described. The goal and predicted 35 String Calculation energy balance based, on the respective energy expenditure If (state 2 or 4) then 80% > % DCI or % EE > 120% validgoals and daily caloric intakevalues, is also utilized as an additional and there is a valid activity to make up the difference comparison factor in user states 4 and 5. The possible user in less than an hour else just based on percent states are shown in Table 3: TABLE 3 State Description 1 A user will not reach energy goal and daily caloric intake is below budget 2 A user has or will have burned more calories than the goal, and daily caloric intake is below budget 3 A user hasn't exercised enough and has eaten too much 4 A user has exceeded caloric intake goals, but energy expenditure should make up for it 5 A user has exceeded caloric intake goals, but energy expenditure goals will not make up for it Calculation (energy expenditure < goal energy expenditure) and (daily caloric intake <= goal daily caloric intake) Where = has a tolerance of ± is 50 calories (energy expenditure >= goal energy expenditure) and (daily caloric intake <= goal daily caloric intake) Where = has a tolerance of ± is 50 calories (energy expenditure < goal energy expenditure) and (daily caloric intake > goal daily caloric intake) Where = has a tolerance of ± is 50 calories (energy expenditure >= goal energy expenditure) and (daily caloric intake > goal daily caloric intake) && (predicted energy balance >= goal energy balance) Where = has a tolerance of ± is 50 calories (energy expenditure >= goal energy expenditure) and (daily caloric intake > goal daily caloric intake) && (predicted energy balance < goal energy balance) Where = has a tolerance of ± is 50 calories Case3:15-cv-02579 Document1-3 Filed06/10/15 Page53 of 64 US 8,398,546 B2 41 42 TABLE 6-continued program, as described above. Using such a factor greatly improves the predictive nature of the estimated daily expen­ diture for an individual. The final factor in predicting a weight-loss trend is a nutrition log. A nutrition log allows a person keeps track of the food they are eating. This records the amount of calories consumed so far during the day. Knowing the amount of calories consumed and a prediction of the amount of calories a person can bum allows the armband sensor device to compute a person's energy balance. Energy balance is the difference between calories burned and calories consumed. If a person is expending more calories than they are consuming, they are on a weight-loss trend. A person who is consuming more calories than they are burning is on a weight-gain trend. An energy balance prediction is an estimate made at any time during the day of a person's actual daily energy balance for that day. Suggestions are provided in the form of intermittent status reports, which take one of three general forms. First, a person may be in compliance to achieve the preset goal. This means that the eneigy balance prediction is within a tolerance range which approximates the daily goal. Second, a person may have already achieved the preset goal. If that user's energy balance indicates that more calories may be burned during the day than have been consumed, the user may be congratulated for surpassing the preset goal. Lastly, a user may have consumed more calories than what is projected to be burned. In this case, the system can calculate how many more calories that user may need to bum to meet the goal. Using the predieted energy expenditureassociated with common activities, such as walking, the system can also make suggestions on methods for achieving the goal within a defined period. For example, a person who needs to burn 100 more calories might be advised to take a 30 minute walk in order to achieve a goal given that the system is aware that such activity can bum the necessary calories. Many people settle into routines, especially during the work week. For example, a person may wake up at about the same time every day, go to work, then exercise after work before going home and relaxing. Their eating patterns may also be similar from day to day. Detecting such similarities in a person's behaviors can allow the armband sensor device to make more accurate predictions about a person's energy bal­ ance and therefore that person's weight-loss trends. There are several ways the energy balance predications can be improved by analyzing an user's past data. First, the amount of rest verses activity in a person's lifestyle can be used to improve the RMR estimate for the remainder of the day. Second, the day can be broken down into time units to improve estimation. For example, a person who normally exercises in the morning and rests in the evening has a differ­ ent daily profile than a person who exercises in the evening. The energy expenditure estimate can be adjusted based on time-of-day to better predict an individual's energy balance. A person's activity may also vary depending on a daily or weekly schedule, the time of the year, or degree of progress toward preset goals. The eneigy expenditure estimate can therefore be adjusted accordingly. Again, this information may be obtained from a time or date management program. Third, creating an average of a person's daily energy expenditure over a certain time can also be used to predict how many calories a person normally bums. Likewise, detecting trends in a person's eating habits can be used to estimate how many calories a person is expected to consume. For example, a person who eats a large breakfast but small dinner has a different profile than a person who skips breakfast but eats a number of small meals during the String Calculation suspectgoals If (state 2 or 4) then 80% > % DCI or % EE > 120% or there is NOT a valid activity to make up the difference in less than an hour else just based on percent 5 where % DCI or % EE represents the current percent of daily caloric intake or energy expenditure, as appropriate, in 1° relation to the goal of the user. A similar method is used to determine the messages below each horizontal bar chart as shown in FIG. 15. The next part of the selection criteria is achievement status, which is deter­ 15 mined by the current value of daily caloric intake or energy expenditure in relation to the goal set by the user. The param­ eters are as follows: TABLE 7 20 String Calculation above even below Value > goal Value = goal Value < goal In alternative embodiments, the representation underlying the method for choosing the feedback could be, but are not limited to being, a decision tree, planning system, constraint satisfaction system, frame based system, case based system rule-based system, predicate calculus, general purpose planning system, or a probabilistic network. In alternative embodiments, another aspect of the method is to adapt the subsystem choosing the feedback. This can be done, for example, using a decision-theoretic adaptive probabilistic system, a simple adaptive planning system, or a gradient descent method on a set of parameters. With respect to the calculation of energy balance, the arm­ band sensor device continuously measures a person's energy expenditure. During the day the human body is continuously burning calories. The minimal rate that a human body expends energy is called resting metabolic rate, or RMR. For an average person, the daily RMR is about 1500 calories. It is more for larger people. Eneigy expenditure is different than RMR because a per­ son knows throughout the day how many calories have been bumed so far, both at rest and when active.At the time when the user views energy expenditure information, two things are known. First, the caloric bum of that individual from midnight until that time of day, as recorded by armband sensor device. Second, that user's RMR from the current time until the end of the day. The sum of these numbers is a prediction of the minimum amount of calories that the user expends during the day. This estimate may be improved by applying a multiplica­ tive factor to RMR. A person's lifestyle contributes greatly to the amount of eneigy they expend. A sedentary person who does not exercise burns calories only slightly more than those consumed by their RMR. An athlete who is constantly active bums significantly more calories than RMR. These lifestyle effects on RMR may be estimated as multiplicative factors to RMR ranging from 1.1 for a sedentary person to 1.7 for an athlete. This multiplicative factormay also calculated from an average measurement of the person's wear time based on the time of day or the time of year, or it may be determined from information a user has entered in date or time management 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page54 of 64 US 8,398,546 B2 43 44 day. These different eating habits can also be reflected in an user's energy balance to provide a more accurate daily esti­ mate. The concept of energy balance is not limited to single days. It may also be applied to multiple days, weeks, months or even years. For example, people often overeat on special occasions such as holidays, birthdays or anniversaries. Such unusual consumption eating spurts may be spurious or may contribute to long-term patterns. Actual energy balance over time can indicate weight-loss or weight-gain trends and help an individual adjust his goal to match actual exercise and eating habits. The logic for the calculation of the intermittent status reports 1140 is provided in the references to FIGS. 16-19. FIG. 16 illustrates the calculation of the intermittent status reports 1140 using information from both the eneigy expen­ diture and caloric intake values. If the intermittent status report status 1150 indicates that an intermittent status report 1140 has already been prepared for today, the intermittent status report program returns the energy balance value 1155 which is the difference between the energy expenditure and the daily caloric intake. An arbitrary threshold, for example 40 calories, is chosen as a goal tolerance to place the user into one of three categories. If the difference between the energy expenditure and the daily caloric intake is greater than +40 calories, a balance status indicator 1160 indicates that the user has significantly exceeded a daily eneigy balance goal for the day. If the difference between the values is less than -40 calories, a balance status indicator 1160 indicates that the user has failed to meet a daily energy balance goal. If the difference between the values is near or equal to 0, as defined by the tolerance between ±40 calories difference, a balance status indicator 1160 indicates that the user has met a daily energy balance goal. The program performs a time check 1165. Depending on whether the current time is before or after an arbitrary time limit, the program determines if it is early or late. Further, the program displays an energy balance goal intermittent status report 1170 indicating whether an indi­ vidual has time to meet their energy balance goal within the time limit of the day or other period, based on the time of day, in addition to a suggestion for an energy expenditure activity to assist in accomplishing the goal, all based upon the prior intermittent status report 1040 for that day. If the intermittent status report status 1150 determines that an intermitted status report 1040 has not been prepared for today, the program retrieves the energy balance value 1155 and determines if the energy expenditure is greater or less than the caloric intake value. Depending on the value of the difference between the eneigy expenditure value and the caloric intake value which is indicated by the balance status indicator 1160, the program performs a user state determina­ tion. The user state determination 1175 is the overall relationship between the user's goal and actual eneigy expenditure for the relevant time periods and the goal and actual daily caloric intake for that same period. After the program determines the user's state, the program determines the goal status 1180 of the user. If the status of the goals is within a certain percentage of completion, the program performs a time deter­ mination 1185 in regard to whether or not the user can still meet these goals, within the time frame, by performing a certain activity. The program displays a relevant energy bal­ ance goal intermittent status report 1170 to the user. The content of intermittent status report 1170 is determined by the outcome of these various determinations and is selected from an appropriate library of reference material. FIG. 17 illustrates the generation of an intermittent status report based only on energy expenditure. If the intermittent status report status 1150 indicates that an intermittent status report 104 has been prepared for the day, the program calcu­ lates the eneigy expenditure goal progress 1190 which is the difference between the goal eneigy expenditure and the current eneigy expenditure. If the energy expenditure exceeds the goal energy expenditure, the program determines any required exercise amount 1195 that may be needed to enable the user to achieve energy expenditure goals for the day. Similarly, if the current or predicted energy expenditure value is less than the goal energy expenditure, the program determines any required exerciseamount 1195 to enable to the user to meet the daily goal. An eneigy expenditure intermittent status report 1200 will be generated based on this information with suggested exercise activity. If an intermittent status report 1040 has not already been prepared for the relevant time period, the intermittent status report status 1150 instructs the program to calculate the energy expenditure goal progress 1190 using the goal and predicted eneigy expenditure values. Based on this value, the program determines any required exercise amount 1195 to enable the user to achieve energy expenditure goals. An energy expenditure intermittent status report 1200a is gener­ ated based on this information with any suggested exercise activity. FIG. 18 illustrates how the program generates an intermit­ tent status report based solely on caloric intake. The caloric status 1205 is calculated, which is the difference between the goal caloric intake and predicted caloric intake. If the pre­ dicted caloric intake is greater than the goal caloric intake, the user has exceeded the caloric budget. If the predicted caloric intake is less than the goal caloric intake the user has con­ sumed less calories than the caloric budget. If the value is near or equal to 0, the user has met their caloric budget. A caloric intake intermittent status report 1210 is generated based on this information, Similarly, FIG.18 illustrates how the program makes a user state status determination 1215 of the user's caloric intake. This calculation may be the same for the determination of the user's state of energy expenditure. The user state status is determined by subtracting the difference between the predieted caloric intake and the goal caloric intake. An arbitrary threshold, for example 50, is chosen as a goal tolerance to place the user into one of three categories. If the difference between the predicted caloric intake and the goal caloric intake is greater than +50 calories, the state status determination result is 1. If the difference between the predicted caloric intake and the goal caloric intake is less than -50 calories, the state status determination result is -1. If the goal amount is greater than the predicted amount, the program returns a negative 1. If the difference between the values is near or equal to 0, as defined by the tolerance between ±50 caloric difference, the state status determination result is 0. Based on the user state status determination described above, FIG. 19 illustrates how the program ultimately makes the user state determination 1175. The program makes a user state status determination 1215 of the user's caloric intake determination based on the above calculation. After the pro­ gram returns the value of 1,0 or -1, the program makes a user state status determination 1215 of the user's eneigy expenditure. Based on the combination of the values, a user state determination 1 175 is calculated. A specific embodiment of sensor device10 is shown which is in the form of an armband adapted to be worn by an individual on his or her upper arm, between the shoulder and the elbow, as illustrated in FIGS. 20-25. Although a similar sensor device may be worn on other parts of the individual's body, these locations have the same function for single or 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page55 of 64 US 8,398,546 B2 45 multi-sensor measurements and for the automatic detection and/or identification of the user's activities or state. For the purpose of this disclosure, the specific embodiment of sensor device 10 shown in FIGS. 20-25 will, for convenience, be referred to as armband sensor device 400. Armband sensor device 400 includes computer housing 405, flexible wing body 410, and, as shown in FIG. 25, elastic strap 415. Com­ puter housing 405 and flexible wing body 410 are preferably made of a flexible urethane material or an elastomeric material such as rubber or a rubber-silicone blend by a molding process. Flexible wing body 410 includes first and second wings 418 each having a thru-hole 420 located near the ends 425 thereof. First and second wings 418 are adapted to wrap around a portion of the wearer's upper arm. Elastic strap 415 is used to removably affix armband sensor device 400 to the individual's upper arm. As seen in FIG. 25, bottom surface 426 of elastic strap 415 is provided with velcro loops 416 along a portion thereof. Each end 427 of elastic strap 415 is provided with velcro hook patch 428 on bottom surface 426 and pull tab 429 on top surface 430. A portion of each pull tab 429 extends beyond the edge of each end 427. In order to wear armband sensor device 400, a user inserts each end 427 of elastic strap 415 into a respective thru-hole 420 of flexible wing body 410. The user then places his arm through the loop created by elastic strap 415, flexible wing body 410 and computer housing 405. By pulling each pull tab 429 and engaging velcro hook patches 428 with velcro loops 416 at a desired position along bottom surface 426 of elastic strap 415, the user can adjust elastic strap 415 to fit comfortably. Since velcro hook patches 428 can be engaged with velcro loops 416 at almost any position along bottom surface 426, armband sensor device 400 can be adjusted to fit arms of various sizes. Also, elastic strap 415 may be provided in various lengths to accommodate a wider range of arm sizes. As will be apparent to one of skill in the art, other means of fastening and adjusting the size of elastic strap may be used, including, but not limited to, snaps, buttons, or buckles. It is also possible to use two elastic straps that fasten by one of several conventional means including velcro, snaps, buttons, buckles or the like, or merely a single elastic strap affixed to wings 418. Alternatively, instead of providing thru-holes 420 in wings 418, loops having the shape of the letter D, not shown, may be attached to ends 425 of wings 418 by one of several conventional means. For example, a pin, not shown, may be inserted through ends 425, wherein the pin engages each end of each loop. Inthis configuration, the D-shaped loops would serve as connecting points for elastic strap 415, effectively creating a thru-hole between each end 425 of each wing 418 and each loop. As shown in FIG. 18, which is an exploded view of armband sensor device 400, computer housing 405 includes a top portion 435 and a bottom portion 440. Contained within computer housing 405 are printed circuit board or PCB 445, rechargeable battery 450, preferably a lithium ion battery, and vibrating motor 455 for providing tactile feedback to the wearer, such as those used in pagers, suitable examples of which are the Model 12342 and 12343 motors sold by MG Motors Ltd. of the United Kingdom. Top portion 435 and bottom portion 440 of computer hous­ ing 405 sealingly mate along groove 436 into which 0-ring 437 is fit, and may be affixed to one another by screws, not shown, which pass through screw holes 438a and stiffeners 4386 of bottom portion 440 and apertures 439 in PCB 445 and into threaded receiving stiffeners 451 of top portion 435. Alternately, top portion 435 and bottom portion 440 may be 46 snap fit together or affixed to one another with an adhesive. Preferably, the assembled computer housing 405 is suffi­ ciently water resistant to permit armband sensor device 400 to be worn while swimming without adversely affecting the 5 performance thereof. As can be seen in FIG. 13, bottom portion 440 includes, on a bottom side thereof, a raised platform 430. Affixed to raised platform 430 is heat flow or flux sensor 460, a suitable example of which is the micro-foil heat flux sensor sold by 10 RdF Corporation of Hudson, N.H. Heat flux sensor 460 func­ tions as a self-generating thermopile transducer, and prefer­ ably includes a carrier made of a polyamide film. Bottom portion 440 may include on a top side thereof, that is on a side opposite the side to which heat flux sensor 460 is affixed, a 15 heat sink, not shown, made of a suitable metallic material such as aluminum. Also affixed to raised platform 430 are GSR sensors 465, preferably comprising electrodes formed of a material such as conductive carbonized rubber, gold or stainless steel. Although two GSR sensors 465 are shown in 20 FIG. 21, it will be appreciated by oneof skill in the artthatthe number of GSR sensors 465 and the placement thereof on raised platform 430 can vary as long as the individual GSR sensors 465, i.e., the electrodes, are electrically isolated from one another. By being affixed to raised platform 430, heat flux 25 sensor 460 and GSR sensors 465 are adapted to be in contact with the wearer's skin when armband sensor device 400 is worn. Bottom portion 440 of computer housing 405 may also be provided with a removable and replaceable soft foam fabric pad, not shown, on a portion of the surface thereof that 30 does not include raised platform 430 and screw holes 438a. The soft foam fabric is intended to contact the wearer's skin and make armband sensor device 400 more comfortable to wear, Electrical coupling between heat flux sensor 460, GSR 35 sensors 465, and PCB 445 may be accomplished in one of various known methods. For example, suitable wiring, not shown, may be molded into bottom portion 440 of computer housing 405 and then electrically connected, such as by soldering, to appropriate input locations on PCB 445 and to heat 40 flux sensor 460 and GSR sensors 465. Alternatively, rather than molding wiring into bottom portion 440, thru-holes may be provided in bottom portion 440 through which appropriate wiring may pass. The thru-holes would preferably be provided with a water tight seal to maintain the integrity of 45 computer housing 405. Rather than being affixed to raised platform 430 as shown in FIG. 21, one or both of heat flux sensor 460 and GSR sensors 465 may be affixed to the inner portion 466 of flexible wing body 410 on either or both of wings 418 so as to be in 50 contact with the wearer's skin when armband sensor device 400 is worn. In such a configuration, electrical coupling between heat flux sensor 460 and GSR sensors 465, whichever the case may be, and the PCB 445 may be accomplished through suitable wiring, not shown, molded into flexible wing 55 body 410 that passes through one or more thru-holes in computer housing 405 and that is electrically connected, such as by soldering, to appropriate input locations on PCB 445. Again, the thru-holes would preferably be provided with a water tight seal to maintain the integrity of computer housing 60 4 05. Alternatively, rather than providing thru-holes in com­ puter housing 405 through which the wiring passes, the wir­ ing may be captured in computer housing 405 during an overmolding process, described below, and ultimately sol­ dered to appropriate input locations on PCB 445. 65 As shown in FIGS. 12, 16, 17 and 18, computer housing 405 includes a button 470 that is coupled to and adapted to activate a momentary switch 585 on PCB 445. Button 470 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page56 of 64 US 8,398,546 B2 47 48 may be used to activate armband sensor device 400 for use, to processing unit 490 and the additional electrical contacts mark the time an event occurred or to request system status provided in battery recharger unit 480 would be coupled to a information suchas battery level and memory capacity. When suitable cable that in turn would be coupled to a serial port, button 470 is depressed, momentary switch 585 closes a such as an RS R32 port or a USB port, of a device such as circuit and a signal is sent to processing unit 490 on PCB 445. 5 personal computer 35. This configuration thus provides an Depending on the time interval for which button 470 is alternate method for uploading of data from and downloading depressed, the generated signal triggers one of the events just of data to armband sensor device 400 using a physical con­ described. Computer housing 405 also includes LEDs 475, nection. which may be used to indicate battery level or memory capac­ FIG. 28 is a schematic diagram that shows the system ity or to provide visual feedback to the wearer. Rather than 10 architecture of armband sensor device 400, and in particular LEDs 475, computer housing 405 may also include a liquid each of the components that is either on or coupled to PCB crystal display or LCD to provide battery level, memory 445. capacity or visual feedback information to the wearer. Battery As shown in FIG. 25, PCB 445 includes processing unit level, memory capacity or feedback information may also be 490, which may be a microprocessor, a microcontroller, or given to the user tactily or audibly. 15 any other processing device that can be adapted to perform Armband sensor device 400 may be adapted to be activated the functionality described herein. Processing unit 490 is for use, that is collecting data, when either of GSR sensors adapted to provide all of the functionality described in con­ 465 or heat flux sensor 460 senses a particular condition that nection with microprocessor 20 shown in FIG. 2. A suitable indicates that armband sensor device 400 has been placed in example of processing unit 490 is the Dragonball EZ sold by contact with the user's skin. Also, armband sensor device 400 20 Motorola, Inc. of Schaumburg, 111. PCB 445 also has thereon may be adapted to be activated for use when one or more of a two-axis accelerometer 495, a suitable example of which is heat flux sensor 460, GSR sensors 465, accelerometer 495 or the Model ADXL210 accelerometer sold by Analog Devices, 550, or any other device in communication with armband Inc. of Norwood; Mass. Two-axis accelerometer 495 is pref­ sensor device 400, alone or in combination, sense a particular erably mounted on PCB 445 at an angle such that its sensing condition or conditions that indicate that the armband sensor 25 axes are offset at an angle substantially equal to 45 degrees from the longitudinal axis of PCB 445 and thus the longitu­ device 400 has been placed in contact with the user's skin for dinal axis of the wearer's arm when armband sensor device use. At other times, armband sensor device 400 would be 400 is worn. The longitudinal axis of the wearer's arm refers deactivated, thus preserving battery power. Computer housing 405 is adapted to be coupled to a battery to the axis defined by a straight line drawn from the wearer's recharger unit 480 shown in FIG. 27 for the purpose of 30 shouldertothewearer'selbow.Theoutputsignalsoftwo-axis recharging rechaigeable battery 450. Computer housing 405 accelerometer 495 are passed through buffers 500 and input into analog to digital converter 505 that in turn is coupled to includes rechaiger contacts 485, shown in FIGS. 12, 15, 16 and 17, that are coupled to rechargeable battery 450. processing unit 490. GSR sensors 465 are coupled to ampli­ Rechaiger contracts 485 may be made of a material such as fier 510 on PCB 445. Amplifier 510 provides amplification brass, gold or stainless steel, and are adapted to mate with and 35 and low pass filtering functionality, a suitable example of which is the Model AD8544 amplifier sold by Analog be electrically coupled to electrical contacts, not shown, pro­ Devices, Inc. of Norwood, Mass. The amplified and filtered vided in battery recharger unit 480 when armband sensor signal output by amplifier 510 is input into amp/offset 515 to device 400 is placed therein. The electrical contacts provided provide further gain and to remove any bias voltage and into in battery recharger unit 480 may be coupled to recharging circuit 481 a provided inside battery rechaiger unit 480. In 40 filter/conditioning circuit 520, which in turn are each coupled to analog to digital converter 505. Heat flux sensor 460 is this configuration, recharging circuit 481 would be coupled to coupled to differential input amplifier 525, such as the Model a wall outlet, such as by way of wiring including a suitable INA amplifier sold by Burr-Brown Corporation of Tucson, plug that is attached or is attachable to battery recharger unit 480. Alternatively, electrical contacts 480 may be coupled to Ariz., and the resulting amplified signal is passed through wiring that is attached to or is attachable to battery recharger 45 filter circuit 530, buffer 535 and amplifier 540 before being input to analog to digital converter 505. Amplifier 540 is unit 480 that in turn is coupled to recharging circuit 481b configured to provide further gain and low pass filtering, a external to battery rechaiger unit 480. The wiring in this suitable example of which is the Model AD8544 amplifier configuration would also include a plug, not shown, adapted sold by Analog Devices, Inc. of Norwood, Mass. PCB 445 to be plugged into a conventional wall outlet. Also provided inside battery rechargerunit 480 is RF trans- 50 also includes thereon a battery monitor 545 that monitors the ceiver 483 adapted to receive signals from and transmit sig­ remaining power level of rechargeable battery 450. Battery nals to RF transceiver 565 provided in computer housing 405 monitor 545 preferably comprises a voltage divider with a and shown in FIG. 28. RF transceiver 483 is adapted to be low pass filter to provide average battery voltage. When a user coupled, for example by a suitable cable, to a serial port, such depresses button 470 in the manner adapted for requesting as an RS 232 port or a USB port, of a device such as personal 55 battery level, processing unit 490 checks the output of battery computer 35 shown in FIG. 1. Thus, data may be uploaded monitor 545 and provides an indication thereof to the user, from and downloaded to armband sensor device 400 using RF preferably through LEDs 475, but also possibly through transceiver 483 and RF transceiver 565. It will be appreciated vibrating motor 455 or ringer 575. An LCD may also be used. that although RF transceivers 483 and 565 are shown in FIGS. PCB 445 may include three-axis accelerometer550 instead 19 and 20, other forms of wireless transceivers may be used, 60 of or in addition to two-axis accelerometer 495. The threesuch as infrared transceivers. Alternatively, computer hous­ axis accelerometer outputs a signal to processing unit 490. A ing 405 may be provided with additional electrical contacts, suitable example of three-axis accelerometer is the jxPAM product soldbyl.M. Systems, Inc. of Scottsdale, Ariz. Threenot shown, that would be adapted to mate with and be elec­ trically coupled to additional electrical contacts, not shown, axis accelerometer 550 is preferably tilted in the manner provided in battery recharger unit 480 when armband sensor 65 described with respect to two-axis accelerometer 495. device 400 is placed therein. The additional electrical con­ PCB 445 also includes RF receiver 555 that is coupled to tacts in the computer housing 405 would be coupled to the processing unit 490. RF receiver 555 may be used to receive Case3:15-cv-02579 Document1-3 Filed06/10/15 Page57 of 64 US 8,398,546 B2 49 50 signals that are output by another device capable of wireless transmission, shown in FIG. 28 as wireless device 558, worn by or located near the individual wearing armband sensor device 400. Located near as used herein means within the transmission range of wireless device 558. For example, wireless device 558 may be a chest mounted heart rate moni­ tor such as the Tempo product sold by Polar Electro of Oulu, Finland. Using such a heart rate monitor, data indicative of the wearer's heart rate can be collected by armband sensor device 400. Antenna 560 and RF transceiver 565 are coupled to processing unit 490 and are provided for purposes of upload­ ing data to central monitoring unit 30 and receiving data downloaded from central monitoring unit 30. RF transceiver 565 and RF receiver 555 may, for example, employ Bluetooth technology as the wireless transmission protocol. Also, other forms of wireless transmission may be used, such as infrared transmission. Vibrating motor 455 is coupled to processing unit 490 through vibrator driver 570 and provides tactile feedback to the wearer. Similarly, ringer 575, a suitable example of which is the Model SMT916A ringer sold by Projects Unlimited, Inc. of Dayton, Ohio, is coupled to processing unit 490 through ringer driver 580, a suitable example of which is the Model MMBTA14 CTI darlington transistor driver sold by Motorola, Inc. of Schaumbuig, 111., and provides audible feedback to the wearer. Feedback may include, for example, celebratory, cautionary and other threshold or event driven messages, such as when a wearer reaches a level of calories burned during a workout. Also provided on PCB 445 and coupled to processing unit 490 is momentary switch 58.5. Momentary switch 585 is also coupled to button 470 for activating momentary switch 585. LEDs 475, used to provide various types of feedback infor­ mation to the wearer, are coupled to processing unit 490 through LED latch/driver 590. Oscillator 595 is provided on PCB 445 and supplies the system clock to processing unit 490. Reset circuit 600, acces­ sible and triggerable through a pin-hole in the side of com­ puter housing 405, is coupled to processing unit 490 and enables processing unit 490 to be reset to a standard initial setting. Rechargeable battery 450, which is the main power source for the armband sensor device 400, is coupled to processing unit 490 through voltage regulator 605. Finally, memory functionality is provided for armband sensor device 400 by SRAM 610, which stores data relating to the wearer of arm band sensor device 400, and flash memory 615, which stores program and configuration data, provided on PCB 445. SRAM 610 and flash memory 615 are coupled to processing unit 490 and each preferably have at least 512K of memory. In manufacturing and assembling armband sensor device 400, top portion 435 of computer housing 405 is preferably formed first, such as by a conventional molding process, and flexible wing body 410 is then overmolded on top of top portion 435. That is, top portion 435 is placed into an appropriately shaped mold, i.e., one that, when top portion 435 is placed therein, has a remaining cavity shaped according to the desired shape of flexible wing body 410, and flexible wing body 410 is molded on top of top portion 435. As a result, flexible wing body 410 and top portion 435 will meige or bond together, forming a single unit. Alternatively, top por­ tion 435 of computer housing 405 and flexible wing body 410 may be formed together, such as by molding in a single mold, to form a single unit. The single unit however formed may then be turned over such that the underside of top portion 435 is facing upwards, and the contents of computer housing 405 can be placed into top portion 435, and top portion 435 and bottom portion 440 can be affixed to one another. As still another alternative, flexible wing body 410 may be separately formed, such as by a conventional molding process, and com­ puter housing 405, and in particular top portion 435 of computer housing 405, may be affixed to flexible wing body 410 by one of several known methods, such as by an adhesive, by snap-fitting, or by screwing the two pieces together. Then, the remainder of computer housing 405 would be assembled as described above. It will be appreciated that rather than assemblingtheremainderofcomputerhousing405aftertopportion 435 has been affixed to flexible wing body 410, the computer housing 405 could be assembled first and then affixed to flexible wing body 410. In a variety of the embodiments described above, it is specifically contemplated that the activity or nutritional data be input or detected by the system for derivation of the nec­ essary data. As identified in several embodiments, the auto­ matic detection of certain activities and/or nutritional intake may be substituted for such manual input. One aspect of the present invention relates to a sophisticated algorithm development process for creating a wide range of algorithms for generating information relating to a variety of variables from the data received from the plurality of physiological and/or contextual sensors on sensor device 400. Such variables may include, without limitation, eneigy expenditure, including resting, active and total values, daily caloric intake, sleep states, including in bed, sleep onset, sleep interruptions, wake, and out of bed, andactivity states, including exercising, sitting, traveling in a motor vehicle, and lying down, and the algorithms for generating values for such variables may be based on data from, for example, the 2-axis accelerometer, the heat flux sensor, the GSR sensor, the skin temperature sensor, the near-body ambient temperature sensor, and the heart rate sensor in the embodiment described above. Note that there are several types of algorithms that can be computed. For example, and without limitation, these include algorithms for predicting user characteristics, continual mea­ surements, durative contexts, instantaneous events, and cumulative conditions. User characteristics include permanent and semi-permanent parameters of the wearer, including aspects such as weight, height, and wearer identity. An example of a continual measurement is energy expenditure, which constantly measures, for example on a minute by minute basis, the number of calories of eneigy expended by the wearer. Durative contexts are behaviors that last some period of time, such as sleeping, driving a car, oqogging. Instantaneous events are those that occur at a fixed or over a very short time period, such as a heart attack or falling down. Cumulative conditions are those where the person's condition can be deduced from their behavior over some previous period of time. For example, if a person hasn't slept in 36 hours and hasn't eaten in 10 hours, it is likely that they are fatigued. Table 8 below shows numerous examples of specific personal characteristics, continual measurements, durative measurements, instantaneous events, and cumulative condi­ tions. 5 10 15 20 25 30 35 40 45 50 55 TABLE 8 60 personal characteristics continual measurements 65 age, sex, weight, gender, athletic ability, conditioning, disease, height, susceptibility to disease, activity level, individual detection, handedness, metabolic rate, body composition mood, beat-to-beat variability of heart beats, respiration, energy expenditure, blood glucose levels, level of ketosis, heart rate, stress levels, fatigue levels, alertness levels, blood pressure, readiness, strength, endurance, amenability to Case3:15-cv-02579 Document1-3 Filed06/10/15 Page58 of 64 US 8,398,546 B2 51 TABLE 8-continued interaction, steps per time period, stillness level, body position and orientation, cleanliness, mood or affect, approachability, caloric intake, TEF, XEF, 'in the zone'-ness, active energy expenditure, carbohydrate intake, fat intake, protein intake, hydration levels, truthfulness, sleep quality, sleep state, consciousness level, effects of medication, dosage prediction, water intake, alcohol intake, dizziness, pain, comfort, remaining processing power for new stimuli, proper use of the armband, interest in a topic, relative durative measurements instantaneous events cumulative conditions exertion, location, blood-alcohol level exercise, sleep, lying down, sitting, standing, ambulation, running, walking, biking, stationary biking, road biking, lifting weights, aerobic exercise, anaerobic exercise, strengthbuilding exercise, mind-centering activity, periods of intense emotion, relaxing, watching TV, sedentary, REM detector, eating, in-thezone, interruptible, general activity detection, sleep stage, heat stress, heat stroke, amenable to teaching/learning, bipolar decompensation, abnormal events (in heart signal, in activity level, measured by the user, etc), startle level, highway driving or riding in a car, airplane travel, helicopter travel, boredom events, sport detection (football, baseball, soccer, etc), studying, reading, intoxication, effect of a drug falling, heart attack, seizure, sleep arousal events, PVCs, blood sugar abnormality, acute stress or disorientation, emergency, heart arrhythmia, shock, vomiting, rapid blood loss, taking medication, swallowing Alzheimer's, weakness or increased likelihood of falling, drowsiness, fatigue, existence of ketosis, ovulation, pregnancy, disease, illness, fever, edema, anemia, having the flu, hypertension, mental disorders, acute dehydration, hypothermia, being-in-the-zone It will be appreciated that the present invention may be utilized in a method for doing automatic journaling of a wearer's physiological and contextual states. The system can automatically produce a journal of what activities the user was engaged in, what events occurred, how the user's physi­ ological state changed over time, and when the user experi­ enced or was likely to experience certain conditions. For example, the system can produce a record of when the user exercised, drove a car, slept, was in danger of heat stress, or ate, in addition to recording the user's hydration level, energy expenditure level, sleep levels, and alertness levels through­ out a day. These detectedconditions can be utilized to time- or event-stamp the data record, to modify certain parameters of the analysis or presentation of the data, as well as trigger certain delayed or real time feedback events. According to the algorithm development process, linear or non-linear mathematical models or algorithms are con­ structed that map the data from the plurality of sensors to a desired variable. The process consists of several steps. First, data is collected by subjects wearing sensor device 400 who are put into situations as close to real world situations as possible, with respect to the parameters being measured, such that the subjects are not endangered and so that the variable that the proposed algorithm is to predict can, at the same time, be reliably measured using, for example, highly accurate medical grade lab equipment. This first step provides the following two sets of data that are then used as inputs to the algorithm development process: (i) the raw data from sensor device 400, and (ii) the data consisting of the verifiably accurate data measurements and extrapolated or derived data made with or calculated from the more accurate lab equip- 52 ment. This verifiable data becomes a standard against which other analytical or measured data is compared. For cases in which the variable that the proposed algorithm is to predict relates to context detection, such as traveling in a motor 5 vehicle, the verifiable standard data is provided by the sub­ jects themselves, such as through information input manually into sensor device 400, a PC, or otherwise manually recorded. The collected data, i.e., both the raw data and the correspond­ ing verifiable standard data, is then organized into a database 10 and is split into training and test sets. Next, using the data in the training set, a mathematical model is built that relates the raw data to the corresponding verifiable standard data. Specifically, a variety of machine learning techniques are used to generate two types of algo15 rithms: 1) algorithms known as features, which are derived continuous parameters that vary in a manner that allows the prediction of the lab-measured parameter for some subset of the data points. The features are typically not conditionally independent of the lab-measured parameter e.g. V02 level 20 information from a metabolic cart, douglas bag, or doubly labeled water, and 2) algorithms known as context detectors that predict various contexts, e.g., running, exercising, lying down, sleeping or driving, useful for the overall algorithm. A number of well known machine learning techniques may be 25 used in this step, including artificial neural nets, decision trees, memory-based methods, boosting, attribute selection through cross-validation, and stochastic search methods such as simulated annealing and evolutionary computation. After a suitable set of features and context detectors are 30 found, several well known machine learning methods are used to combine the features and context detectors into an overall model. Techniques used in this phase include, but are not limited to, multilinear regression, locally weighted regression, decision trees, artificial neural networks, stochas35 tic search methods, support vector machines, and model trees. These models are evaluated using cross-validation to avoid over-fitting. At this stage, the models make predictions on, for example, a minute by minute basis. Inter-minute effects are next taken 40 into account by creating an overall model that integrates the minute by minute predictions. A well known or custom win­ dowing and threshold optimization tool may be used in this step to take advantage of the temporal continuity of the data. Finally, the model's performance can be evaluated on the test 45 set5 which has not yet been used in the creation of the algorithm. Performance of the model on the test set is thus a good estimate of the algorithm's expected performance on other unseen data. Finally, the algorithm may undergo live testing on new data for further validation. 50 Further examples of the types of non-linear functions and/ or machine learning method that may be used in the present invention include the following: conditionals, case state­ ments, logical processing, probabilistic or logical inference, neural network processing, kernel based methods, memory55 based lookup including kNN and SOMs, decision lists, decision-tree prediction, support vector machine prediction, clus­ tering, boosted methods, cascade-correlation, Boltzmarm classifiers, regression trees, case-based reasoning, Gaussians, Bayes nets, dynamic Bayesian networks, HMMs, Kalman 60 filters, Gaussian processes and algorithmic predictors, e.g. learned by evolutionary computation or other program syn­ thesis tools. Although one can view an algorithm as taking raw sensor values or signals as input, performing computation, and then 65 producing a desired output, it is useful in one preferred embodiment to view the algorithm as a series of derivations that are applied to the raw sensor values. Each derivation Case3:15-cv-02579 Document1-3 Filed06/10/15 Page59 of 64 US 8,398,546 B2 53 54 produces a signal referred to as a derived channel. The raw sensor values or signals are also referred to as channels, specifically raw channels rather than derived channels. These derivations, also referred to as functions, can be simple or complex but are applied in a predetermined order on the raw values and, possibly, on already existing derived channels. The first derivation must, of course, only take as input raw sensor signals and other available baseline information such as manually entered data and demographic information about the subject, but subsequent derivations can take as input previously derived channels. Note that one can easily determine, from the order of application of derivations, the particular channels utilized to derive a given derived channel. Also note that inputs that a user provides on an Input/Output, or I/O, device or in some fashion can also be included as raw signals which can be used by the algorithms. For example, the cat­ egory chosen to describe a meal can be used by a derivation that computes the caloric estimate for the meal. In one embodiment, the raw signals are first summarized into chan­ nels that are sufficient for later derivations and can be efficiently stored. These channels include derivations such as summation, summation of differences, and averages. Note that although summarizing the high-rate data into com­ pressed channels is useful both for compression and for stor­ ing useful features, it may be useful to store some or all segments of high rate data as well, depending on the exact details of the application. In one embodiment, these summary channels are then calibrated to take minor measurable differences in manufacturing into account and to result in values in the appropriate scale and in the correct units. For example, if, during the manufacturing process, a particular temperature sensor was determined to have a slight offset, this offset can be applied, resulting in a derived channel expressing tempera­ ture in degrees Celsius. For purposes of this description, a derivation or function is linear if it is expressed as a weighted combination of its inputs together with some offset. For example, if G and H are two raw or derived channels, then all derivations of the form A*G+B*H+C, where A, B, and C are constants, is a linear derivation. A derivation is non-linear with respect to its inputs if it can not be expressed as a weighted sum of the inputs with a constant offset. An example of a nonlinear derivation is as follows: if G>7 then return H*9, else return H*3.5±912. A channel is linearly derived if all derivations involved in com­ puting it are linear, and a channel is nonlinearly derived if any of the derivations used in creating it are nonlinear. A channel nonlinearly mediates a derivation if changes in the value of the channel change the computation performed in the deriva­ tion, keeping all other inputs to the derivation constant. According to a preferred embodiment of the present invention, the algorithms that are developed using this process will have the format shown conceptually in FIG. 29. Specifically, the algorithm will take as inputs the channels derived from the sensor data collected by the sensor device from the various sensors, and demographic information for the individual as shown in box 1600. The algorithm includes at least one con­ text detector 1605 that produces a weight, shown as W1 through WN, expressing the probability that a given portion of collected data, such as is collected over a minute, was collected while the wearer was in each of several possible contexts. Such contexts may include whether the individual was at rest or active. In addition, for each context, a regression algorithm 1610 is provided where a continuous prediction is computed taking raw or derived channels as input. The indi­ vidual regressions can be any of a variety of regression equations or methods, including, for example, multivariate linear or polynomial regression, memory based methods, support vector machine regression, neural networks, Gaussian pro­ cesses, arbitrary procedural functions and the like. Each regression is an estimate of the output of the parameter of interest in the algorithm, for example, energy expenditure. Finally, the outputs of each regression algorithm 1610 for each context, shown as A1 through AN, and the weights W1 through WN are combined in a post-processor 1615 which outputs the parameter of interest being measured or predicted by the algorithm, shown in box 1620. In general, the postprocessor 1615 can consist of any of many methods for combining the separate contextual predictions, including commit­ tee methods, boosting, voting methods, consistency checking, or context based recombination. Referring to FIG. 30, an example algorithm for measuring energy expenditure of an individual is shown. This example algorithm may be run on sensor device 400 having at least an accelerometer, a heat flux sensor and a GSR sensor, or an I/O device 1200 that receives data from such a sensor device as is disclosed in co-pending U.S. patent application Ser. No. 10/682,75 9, the specification of which is incorporated herein by reference. In this example algorithm, the raw data from the sensors is calibrated and numerous values based thereon, i.e., derived channels, are created. In particular, the following derived channels, shown at 1600 in FIG. 30, are computed from the raw signals and the demographic information: (1) longitudinal accelerometer average, or LAVE, based on the accelerometer data; (2) transverse accelerometer sum of aver­ age differences, or TSAD, based on the accelerometer data; (3) heat flux high gain average variance, or HFvar, based on heat flux sensor data; (4) vector sum of transverse and longitudinal accelerometer sum of absolute differences or SADs, identified as VSAD, based on the accelerometer data; (5) galvanic skin response, or GSR, in both low and combined gain embodiments; and (6) Basal Metabolic Rate or BMR, based on demographic information input by the user. Context detector 1605 consists of a naive Bayesian classifier that predicts whether the wearer is active or resting using the LAVE, TSAD, and HFvar derived channels. The output is a probabilistic weight, W1 andW2 for the two contexts rest and active. For the rest context, the regression algorithm1610 is a linear regression combining channels derived from the accel­ erometer, the heat flux sensor, the user's demographic data, and the galvanic skin response sensor. The equation, obtained through the algorithm design process, is A*VSAD+ B*HFvar+C*GSR+D*BMR+E, where A, B, C, D and E are constants. The regression algorithm 1610 for the active con­ text is the same, except that the constants are different. The post-processor 1615 for this example is to add together the weighted results of each contextual regression. If A1 is the result of the rest regression and A2 is the result of the active regression, then the combination is just W1*A1+W2*A2, which is eneigy expenditure shown at 1620. In another example, a derived channel that calculates whether thewearer is motoring, that is, driving in a car at the time period in question might also be input into the post-processor 1615. The process by which this derived motoring channel is com­ puted is algorithm 3. The post-processor 1615 in this case might then enforce a constraint that when the wearer is pre­ dicted to be driving by algorithm 3, the eneigy expenditure is limited for that time period to a value equal to some factor, e.g. 1.3 times their minute by minute basal metabolic rate. This algorithm development process may also be used to create algorithms to enable sensor device 400 to detect and measure various other parameters, including, without limitation, the following: (i) when an individual is suffering from duress, including states of unconsciousness, fatigue, shock, drowsiness, heat stress and dehydration; and (ii) an individu- 5 10 15 20 25 30 35 40 45 50 55 60 65 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page60 of 64 US 8,398,546 B2 55 56 al's state of readiness, health and/or metabolic status, such as exhaustion and heat exhaustion, among others. The sensor in a military environment, including states of dehydration, device is able to observe a vector of raw signals consisting of under-nourishment and lack of sleep. In addition, algorithms the outputs of certain of the one or more sensors, which may may be developed for other purposes, such as filtering, signal include all of such sensors or a subset of such sensors. As clean-up and noise cancellation for signals measured by a 5 described above, certain signals, referred to as channels same sensor device as described herein. As will be appreciated, the potential terminology problem here as well, may be derived actual algorithm or function that is developed using this from the vector of raw sensor signals as well. A vector X of certain of these raw and/or derived channels, referred to method will be highly dependent on the specifics of the sensor herein as the raw and derived channels X, will change in some device used, such as the specific sensors and placement thereof and the overall structure and geometry of the sensor 10 systematic way depending on or sensitive to the state, event device. Thus, an algorithm developed with one sensor device and/or level of either the state parameterY that is of interest or will not work as well, if at all, on sensor devices that are not some indicator of Y, referred to as U, wherein there is a substantially structurally identical to the sensor device used to relationship between Y and U such that Y can be obtained create the algorithm. from U. According to the present invention, a first algorithm Another aspect of the present invention relates to the ability 15 or function fl is created using the sensor device that takes as of the developed algorithms to handle various kinds of uncer­ inputs the raw and derived channels X and gives anoutput that tainty. Data uncertainty refers to sensor noise and possible predicts and is conditionally dependent, expressed with the sensor failures. Data uncertainty is when one cannot fully symbol T , on (i) either the state parameterY or the indicator trust the data. Under such conditions, for example, if a sensor, U, and (ii) some other state parameter(s) Z of the individual. for example an accelerometer, fails, the system might con- 20 This algorithm or function fl may be expressed as follows: elude that the wearer is sleeping or resting or that no motion fl(X) T U+Z is taking place. Under such conditions it is very hard to conclude if the data is bad or if themodel that is predicting and making the conclusion is wrong. When an application or involves both model and data uncertainties, it is very impor- 25 tant to identify the relative magnitudes of the uncertainties fl(X) T Y+Z associated with data and the model. An intelligent system According to the preferred embodiment, fl is developed would notice that the sensor seems to be producing erroneous using the algorithm development process described elsedata and would either switch to alternate algorithms or would, in some cases, be able to fill the gaps intelligently before 30 where herein which uses ^ specifically the raw and derived channels X, derived from the signals collected by the making any predictions. When neither of these recovery tech­ sensor device, the verifiable standard data relating to U or Y niques are possible, as was mentioned before, returning a and Z contemporaneously measured using a method taken to clear statement that an accurate value can not be returned is be the correct answer, for example highly accurate medical often much preferable to returning information from an algo­ rithm that has been determined to be likely to be wrong. 35 grade lab equipment, and various machine learning techDetermining when sensors have failed and when data channiques to generate the algorithms from thecollected data. The nels are no longer reliable is a non-trivial task because a failed algorithm or function fl is created under conditions where the sensor can sometimes result in readings that may seem conindicator U or state parameterY, whichever the case may be, sistent with some of the other sensors and the data can also fall present. As will be appreciated, the actual algorithm or 40 function that is developed using this method will be highly within the normal operating range of the sensor. dependent on the specifics of the sensor device used, such as Clinical uncertainty refers to the fact that different sensors the specific sensors and placement thereof and the overall might indicate seemingly contradictory conclusions. Clinical structure and geometry of the senor device. Thus, an algo­ uncertainty is when one cannot be sure of the conclusion that rithm developed with one sensor device will not work as well, is drawn from the data. For example, the accelerometers might indicate that the wearer is motionless, leading toward a 45 if at all, on sensor devices that are not substantially structur­ ally identical to the sensor device used to create the algorithm conclusion of a resting user, the galvanic skin response sensor or at least can be translated from device to device or sensor to might provide a very high response, leading toward a conclu­ sensor with known conversion parameters. sion of an active user, the heat flow sensor might indicate that Next, a second algorithm or function f2 is created using the the wearer is still dispersing substantial heat, leading toward a conclusion of an active user, and the heart rate sensor might 50 sensor device that takes as inputs the raw and derived chan­ nels X and gives an output that predicts and is conditionally indicate that the wearer has an elevated heart rate, leading dependent on everything output by fl except either Y or U, toward a conclusion of an active user. An inferior system whichever the case may be, and is conditionally independent, might simply try to vote among the sensors or use similarly indicated by the symbol , of either Y or U, whichever the unfounded methods to integrate the various readings. The present invention weights the important joint probabilities 55 case may be. The idea is that certain of the raw and derived channels X from the one or more sensors make it possible to and determines the appropriate most likely conclusion, which explain away or filter out changes in the raw and derived might be, for this example, that the wearer is currently per­ channels X coming from non-Y or non-U related events. This forming or has recently performed a low motion activity such algorithm or function f2 may be expressed as follows: as stationary biking. According to a further aspect of the present invention, a 60 f2(X) T Z and (f2(X) -U- Y or fL2(X) -U- U sensor device such as sensor device 400 may be used to automatically measure, record, store and/or report a param­ Preferably, f2, like fl, is developed using the algorithm eterY relating to the state of a person, preferably a state of the development process referenced above. f2, however, is devel­ person that cannot be directly measured by the sensors. State oped and validated under conditions where U orY, whichever parameterY may be, for example and without limitation, 65 the case may, is not present. Thus, the gold standard data used calories consumed, energy expenditure, sleep states, hydra­ to create f2 is data relating to Z only measured using highly tion levels, ketosis levels, shock, insulin levels, physical accurate medical grade lab equipment. Case3:15-cv-02579 Document1-3 Filed06/10/15 Page61 of 64 US 8,398,546 B2 57 58 Thus, according to this aspect of the invention, two func­ ally dependent on and predicts the item U of interest, which is tions will have been created, one of which, fl, is sensitive to TEF. In addition, fl is conditionally dependent on and pre­ U or Y, the other of which, f2, is insensitive to U or Y. As will dicts Z which, in this case, is BMR+AE+AT. Next, the sensor be appreciated, there is a relationship between fl and f2 that device is used to create f2, which is an algorithm for predictwill yield either U or Y, whichever the case may be. In other 5 ing all aspects of TEE except for TEF. f2 is developed and words, there is a function f3 such that f3 (fl, f2)=U or f3 (fl, validated on subjects who fasted for a period of time prior to f2)=Y. For example, U or Y may be obtained by subtracting the collection of data, preferably 4-6 hours, to ensure that TEF the data produced by the two functions (U=fl-f2 or Y=flwas not present and was not a factor. Such subjects will be f2). In the case where U, rather thanY, is determined from the performing physical activity without any TEF effect. As a relationship between fl and f2, the next step involves obtain- 10 result, f2 is conditionally dependent to and predicts BMR+ ing Y from U based on the relationship between Y and U. For AE+AT but is conditionally independent of and does not example, Y may be some fixed percentage of U such that Y predict TEF. As such, f2 is referred to as EE(fast) to represent can be obtained by dividing U by some factor. that it predicts energy expenditure not including eating effects. Thus, fl so developed will be sensitive to TEF and f2 One skilled in the art will appreciate that in the present invention, more than two such functions, e.g. (fl, f2, f3, . . . 15 so developed will be insensitive to TEF. As will be apprecif_n-1) could be combined by a last function f_n in the manner ated, in this embodiment, the relationship between fl and f2 described above. In general, this aspect of the invention that will yield the indicator U, which in this case is TEF, is requires that a set of functions is combined whose outputs subtraction. In other words, EE (gorge)-EE (fast)=TEF. vary from one another in a way that is indicative of the Once developed, functions ^ and f2 can be programmed parameter of interest. It will also be appreciated that condi- 20 into software stored by the sensor device and executed by the processor of the sensor device. Data from which the raw and tional dependence or independence as used here will be derived channels X can be derived can then be collected by defined to be approximate rather than precise. The method just described may, for example, be used to the sensor device. The outputs of fj and f2 using the collected automatically measure and/or report the caloric consumption data as inputs can then be subtracted to yield TEF. Once TEF or intake of a person using the sensor device, such as that 25 is determined for a period of time such as a day, calories consumed can be obtained for that period by dividing TEF by person's daily caloric intake, also known as DCI. Automatic 0.1, since TEF is estimated to be 10% of the total calories measuring and reporting of caloric intake would be advanta­ consumed. The caloric consumption data so obtained may be geous because other non-automated methods, such as keep­ stored, reported and/or used in lieu of the manually collected ing diaries and journals of food intake, are hard to maintain and because caloric information for food items is not always 30 caloric consumption data utilized in the embodiments described elsewhere herein. reliable or, as in the case of a restaurant, readily available. It is known that total body metabolism is measured as total Preferably, the sensor device is in communication with a energy expenditure (TEE) according to the following equa­ body motion sensor such as an accelerometer adapted to tion: generate data indicative of motion, a skin conductance sensor 35 such as a GSR sensor adapted to generate data indicative of TEE=BMR+AE+TEF+AT, the resistance of the individual's skin to electrical current, a wherein BMR is basal metabolic rate, which is the energy heat flux sensor adapted to generate data indicative of heat expended by the body during rest such as sleep, AE is activity flow off the body, a body potential sensor such as an ECG energy expenditure, which is the energy expended during sensor adapted to generate data indicative of the rate or other physical activity, TEF is thermic effect of food, which is the 40 characteristics of the heart beats of the individual, and a temperature sensor adapted to generate data indicative of a energy expendedwhile digesting and processing the food that temperature of the individual's skin. In this preferred embodi­ is eaten, and AT is adaptive thermogenesis, which is a mecha­ ment, these signals, in addition the demographic information nism by which the body modifies its metabolism to extreme temperatures. It is estimated that it costs humans about 10% about the wearer, make up the vector of signals from which of the value of food that is eaten to process the food. TEF is 45 the raw and derived channels X are derived. Most preferably, this vector of signals includes data indicative of motion, resis­ therefore estimated to be 10% of the total calories consumed. Thus, a reliable and practical method of measuring TEF tance of the individual's skin to electrical current and heat would enable caloric consumption to be measured without flow off the body. the need to manually track or record food related information. As a limiting case of attempting to estimate TEF as Specifically, once TEF is measured, caloric consumption can 50 described above, one can imagine the case where the set of be accurately estimated by dividing TEF by 0.1 additional state parameters Z is zero. This results in measur­ (TEF=0.1*Calories Consumed; Calories Consumed=TEF/ ing TEF directly through the derivational process using linear and non-linear derivations described earlier. In this variation, 0.1). According to a specific embodiment of the present inven­ the algorithmic process is used to predict TEF directly, which tion relating to the automatic measurement of a state param- 55 must be provided as the verifiable-standard training data, eter Y as described above, a sensor device as described above As an alternative to TEF, any effect of food on the body, may be used to automatically measure and/or record calories such as, for example, drowsiness, urination or an electrical consumed by an individual. In this embodiment, the state effect, or any other signs of eating, such as stomach sounds, parameter Y is calories consumed by the individual and the may be used as the indicator U in the method just described indicatorU is TEF. First, the sensor device is used to create fl, 60 for enabling the automatic measurement of caloric consumpwhich is an algorithm for predicting TEE. fl is developed and tion. The relationship between U and the state parameter Y, validated on subjects who ate food, in other words, subjects which is calories consumed, may, in thesealternative embodi­ who were performing activity and who were experiencing a ments, be based on some known or developed scientific prop­ TEF effect. As such, fl is referred to as EE(gorge) to represent erty or equation or may be based on statistical modeling that it predicts eneigy expenditure including eating effects. 65 techniques. The verifiable standard data used to create fl is a V02 As an alternate embodiment, DCI can be estimated by machine. The function fl, which predicts TEE, is conditioncombining measurements of weight taken at different times Case3:15-cv-02579 Document1-3 Filed06/10/15 Page62 of 64 US 8,398,546 B2 59 60 with estimates of energy expenditure. It is known from the The terms and expressions which have been employed literature that weight change (measured multiple times under herein are used as terms of description and not as limitation, the same conditions so as to filter out effects of water retention and there is no intention in the use of such terms and expres­ and the digestive process) is related to energy balance and sions of excluding equivalents of the features shown and caloric intake as follows: (Caloric Intake-Energy Expendi- 5 described or portions thereof, it being recognized that various ture)/K=weight gain in pounds, where K is a constant prefer­ modifications are possible within the scope of the invention ably equal to 3500. Thus, given that an aspect of the present claimed. Although particular embodiments of the present invention relates to a method and apparatus for measuring invention have been illustrated in the foregoing detailed energy expenditure that may take input from a scale, the description, it is to be further understood that the present caloric intake of a person can be accurately estimated based 10 invention is not to be limited to just the embodiments dison the following equation: Caloric Intake=Eneigy Expendiclosed, but that they are capable of numerous rearrangements, ture+(weigh gain inpounds*K).This methodrequires that the modifications and substitutions. user weigh themselves regularly, but requires no other effort What is claimed is: on their part to obtain a measure of caloric intake. Also note also that DCI can be estimated using an algo- 15 1. A system to provide feedback for an individual's weightrithm that takes sensor data and attempts to directly estimate loss goal, said system comprising: the calories consumed by the wearer, using that number of a. a wearable sensor device for detecting data; and calories as the verifiable standard and the set of raw and b. a processing unit in electronic communication with said derived channels as the training data. This is just an instance sensor device, said processing unit configured to accom­ of the algorithmic process described above. plish the following steps, thus providing said feedback: 20 Another specific instantiation where the present invention (i) derive physiological and contextual data of the indi­ can be utilized relates to detecting when a person is fatigued. vidual from data detected by said sensor device; Such detection can either be performed in at least two ways. (ii) prompt said individual to establish a weight-loss goal; A first way involves accurately measuring parameters such as (iii) generate a first suggestion to engage in an activity to their caloric intake, hydration levels, sleep, stress, and energy 25 assist said individual to achieve said weight-loss goal; expenditure levels using a sensor device and using the two (iv) determine weight-loss; function (^ and f2) approach described with respect to TEF (v) generate a second suggestion to engage in an activity and caloric intake estimation to provide an estimate of to assist said individual to achieve said weight-loss fatigue. A second way involves directly attempting to model goal if said weight-loss goal is not progressing toward fatigue using the direct derivational approach described in 30 the goal; connection with FIGS. 29 and 30. This example illustrates wherein said second suggestion is based upon a determi­ that complex algorithms that predict the wearer's physiologic nation of whether or not the individual complied with state can themselves be used as inputs to other more complex said first suggestion; and algorithms. One potential application for such an embodi­ wherein said determination of whetheror not the individual ment of the present invention would be for first-responders 35 complied with said first suggestion is based on said (e.g. firefighters, police, soldiers) where the wearer is subject derived physiological and contextual data of the indi­ to extreme conditions and performance matters significantly. vidual. In a pilot study, the assignee of the present invention analyzed 2. The system of claim 1, wherein said processing unit is data from firefighters undergoing training exercises and determined that reasonable measures of heat stress were pos- 40 further configured to derive an energy balance from said sible using combinations of calibrated sensor values. For detected data. 3. The system of claim 2, wherein the energy balance is example, if heat flux is too low for too long a period of time derived from daily caloric intake and energy expenditure. but skin temperature continues to rise, the wearer is likely to 4. The system of claim 3, wherein said feedback comprises have a problem. It will be appreciated that algorithms can use both calibrated sensor values and complex derived algo- 45 the effect of daily caloric intake and energy expenditure upon each other. rithms. According to an alternate embodiment of the present 5. The system of claim 2, wherein said processing unit is invention, rather than having the software that implements ^ configured to utilize said eneigy balance to track and predict and f2 and determines U and/or Y therefrom be resident on changes in human physiological parameters. and executed by the sensor device itself, such software may 50 6. The system of claim 1, wherein said processing unit is be resident on and run by a computing device separate from further configured to identify a pattern of behavior from said detected data, to determine whether said pattern affects said the sensor device. In this embodiment, the computing device user's progress, and to adapt said identified pattern of behav­ receives, by wire or wirelessly, the signals collected by the sensor device from which the set of raw and derived channels ior. X are derived and determines Uand/orY from those signals as 55 7. The system of claim 6, wherein said pattern is recorded described above. This alternate embodiment may be an for future review. embodiment wherein the state parameter Y that is determined 8. The system of claim 7, wherein said processing unit is by the computing device is calories consumed and wherein further configured to analyze said recorded patterns to detect the indicator is some effect on the body of food, such as TEF. one of: (i) current and (ii) future patterns of negative, positive The computing device may display the determined caloric 60 and neutral human physiological status parameters, consumption data to the user. In addition, the sensor device 9. The system of claim 8, wherein said analysis of recorded may also generate caloric expenditure data as described else­ patterns are based on one of (i) data from the individual's where herein which is communicated to the computing personal history and (ii) aggregate data of other individuals. device. The computing device may then generate and display 10. The system of claim 1, further comprising a database information based on the caloric consumption data and the 65 comprising data, caloric expenditure data, such as energy balance data, goal 11. The system of claim 10, wherein said database includes related data, and rate of weight loss or gain data. patterns of physiological data. Case3:15-cv-02579 Document1-3 Filed06/10/15 Page63 of 64 US 8,398,546 B2 61 62 12. The system of claim 10, wherein said database includes patterns of contextual data. 13. The system of claim 10, wherein said database includes patterns of activity data derived from said detected data. 14. The system of claim 10, wherein said processing unit is further configured to analyze said data in databaseto establish data patterns. 15. The system of claim 14, wherein said processing unit is further configured to instruct said system to store said data patterns. 16. The system of claim 15, wherein said processing unit is further configured to compare stored data patterns to detected data to identify and categorize said detected data into addi­ tional data patterns. 17. The system of claim 15, wherein said processing unit is further configured to (i) compare stored data patterns to detected data to identify such detected data as being similar to at least one of said stored data patterns and (ii) predict future data. 18. The system of claim 17, wherein said processing unit is configured to generate output based upon said prediction of said future data. 19. The system of claim 18, wherein said output is an alarm. 20. The system of claim 18, wherein said output is a report. 21. The system of claim 18, wherein said output is utilized as input by another device. 22. The system of claim 1, wherein said processing unit is further configured to utilize said feedback for the purpose of establishing an initial assessment for a health modification plan. 23. The system of claim 22, wherein said processing unit is further configured to utilize said feedback for assessing interim status of progress toward said health modification plan. 24. The system of claim 1, wherein said first suggestion comprises a plan. 25. The system of claim 1, further comprising an algorithm stored in a memory of the processing unit, the algorithm configured to calculate weight loss or weight gain using inputs from at least one of the sensor and the individual. 26. The system of claim 1, wherein said processing unit is further configured to derive eneigy expenditure data from said detected data. 27. The system of claim 26, wherein said processing unit is further configured to utilize said eneigy expenditure data to track and predict changes in the individual's human physi­ ological parameters. 28. The system of claim 1, wherein the system is config­ ured for use in the management of at least one of sleep, pregnancy,, diabetes, cardiovascular disease, wellness, and stress. 29. The system of claim 1, wherein said sensor device comprises at least oneof a weight scale and a glucose monitor. 5 10 15 20 25 Case3:15-cv-02579 Document1-3 Filed06/10/15 Page64 of 64 UNITED STATES PATENT AND TRADEMARK OFFICE CERTIFICATE OF CORRECTION PATENT NO. APPLICATION NO. DATED INVENTOR(S) 8,398,546 B2 10/940214 March 19, 2013 Pacione et al. Page 1 of 1 It is certified that error appears in the above-identified patent and that said Letters Patent is hereby corrected as shown below: On the Title Page: The first or sole Notice should read ~ Subject to any disclaimer, the term of this patent is extended or adjusted under 35 U.S.C. 154(b) by 486 days. Signed and Sealed this Second Day of December, 2014 SL Michelle K. Lee Deputy Director of the United States Patent and Trademark Office