Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 1 of 25 PageID #: 12
`I 1111111111111111 11111 1111111111 11111 1111111111 1111111111 lll111111111111111
`US009757066B2
`
`c12) United States Patent
`McGilvery et al.
`
`(IO) Patent No.:
`(45) Date of Patent:
`
`US 9,757,066 B2
`*Sep.12,2017
`
`(54) METRICS ASSESSMENT SYSTEM FOR
`HEALTH, FITNESS AND LIFESTYLE
`BEHAVIORAL MANAGEMENT
`
`(71) Applicant: Fat Statz LLC, Laguna Niguel, CA
`(US)
`
`(72)
`
`Inventors: Justin McGilvery, Laguna Niguel, CA
`(US); Dale E. Mitbo, Orange, CA (US)
`
`(73) Assignee: Fat Statz LLC, Laguna Niguel, CA
`(US)
`
`( *) Notice:
`
`Subject to any disclaimer, the term ofthis
`patent is extended or adjusted under 35
`U.S.C. 154(b) by O days.
`
`This patent is subject to a terminal dis(cid:173)
`claimer.
`
`(21) Appl. No.: 15/401,922
`
`(22) Filed:
`
`Jan. 9, 2017
`
`(65)
`
`Prior Publication Data
`
`US 2017/0112432 Al
`
`Apr. 27, 2017
`
`(63)
`
`(51)
`
`(52)
`
`Related U.S. Application Data
`
`Continuation of application No. 15/199,513, filed on
`Jun. 30, 2016, now abandoned, which
`is a
`(Continued)
`
`Int. Cl.
`A61B 5100
`G09B 19100
`
`(2006.01)
`(2006.01)
`(Continued)
`
`U.S. Cl.
`CPC ............ A61B 51486 (2013.01); A61B 510002
`(2013.01); A61B 51024 (2013.01); A61B 51112
`(2013.01); A61B 514806 (2013.01); A61B
`
`514866 (2013.01); A61B 514872 (2013.01);
`G06F 191345 (2013.01); G06F 1913418
`(2013.01); G06F 1913475 (2013.01); G06F
`1913487 (2013.01); G06F 191363 (2013.01);
`G06Q 50122 (2013.01); G06Q 50124
`(2013.01); G09B 5102 (2013.01); G09B 7106
`(2013.01); G09B 1910038 (2013.01); G09B
`1910092 (2013.01)
`
`(58) Field of Classification Search
`CPC .... G06Q 50/22; G06Q 50/24; G06F 19/3475;
`G06F 19/3487; G06F 19/345; G06F
`19/363
`USPC .......................................................... 434/127
`See application file for complete search history.
`
`(56)
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`
`7,647,234 Bl
`7,953,613 B2
`
`1/2010 Ruderman et al.
`5/2011 Gizewski
`(Continued)
`
`OTHER PUBLICATIONS
`
`Adult BMI. <URL:http://www.cdc.gov/healthyweight/assessing/
`bmi/adult_bmi/> [Retrieved Jul. 27, 2015 1:53:09 PM from US
`Center for Disease Control website, www.cdc.gov].
`(Continued)
`
`Primary Examiner - Nikolai A Gishnock
`(74) Attorney, Agent, or Firm - Knobbe Martens Olson
`& Bear LLP
`
`ABSTRACT
`(57)
`A software and hardware system is described that enables
`effective lifestyle management by providing a dynamic
`assessment of a user's physical and behavioral metrics via a
`high feedback ratio interface.
`
`17 Claims, 15 Drawing Sheets
`
`Your Results
`3/5/2009
`Date
`214.8 Pounds
`Weight
`Body Fat
`45.4%
`1,805.6
`Metabolism
`35.7
`BMI
`Lean Mass 117.2 Pounds
`Fat Mass
`97.6 Pounds
`
`Choose One
`My Measurements
`
`jWeight vi
`
`Compare To:
`IE] My Gender
`0 MyAge
`0 My Height
`0 My Body Type
`
`150.-----------~---_-_-_-_-_-_-_-_-~~
`Members: 6000
`Gender Female
`
`100
`
`50
`
`Current Weight:
`Weight Position:
`
`214.8 lbs.
`97
`
`Median Weight:
`
`136Ibs.
`
`O other members has the same value as you
`5,919 members have a lower value than you
`180 members have a higher value than you
`50% of members have a higher value and 50% of
`members have a lower value
`
`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 2 of 25 PageID #: 13
`
`US 9,757,066 B2
`Page 2
`
`Related U.S. Application Data
`
`continuation of application No. 12/717,811, filed on
`Mar. 4, 2010, now Pat. No. 9,400,872.
`
`(60) Provisional application No. 61/157,856, filed on Mar.
`5, 2009.
`
`(51)
`
`Int. Cl.
`G09B 5102
`G09B 7106
`A61B 51024
`A61B 5111
`G06F 19100
`G06Q 50122
`G06Q 50124
`
`(2006.01)
`(2006.01)
`(2006.01)
`(2006.01)
`(2011.01)
`(2012.01)
`(2012.01)
`
`(56)
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`
`7,959,567 B2 * 6/2011 Stivoric
`
`A61B 5/411
`128/921
`7,974,881 B2 * 7/2011 Culver ................ G06F 19/3475
`426/72
`
`2002/0066602 Al
`2002/0087054 Al
`2002/0128914 Al
`2002/0139588 Al
`2003/0024745 Al
`2003/0055461 Al
`2003/0059747 Al
`2003/0208108 Al
`2003/0208113 Al
`2003/0208409 Al
`2003/0212579 Al
`2003/0229514 A2
`2004/0044560 Al
`2004/0131997 Al
`2004/0148127 Al
`2005/0006152 Al
`2005/0038326 Al
`2005/0228692 Al
`2005/0234742 Al
`2006/0129432 Al
`2007 /0026365 Al
`2007/0100666 Al
`2008/0004904 Al
`2008/0162352 Al
`2008/0275309 Al
`2009/0326981 Al
`2010/0076787 Al
`2012/0010897 Al
`2012/0303381 Al
`
`6/2002 Bliss et al.
`7/2002 Lin et al.
`9/2002 Sansone
`10/2002 Brandt
`2/2003 Huitt et al.
`3/2003 Girouard et al.
`3/2003 Yoshida et al.
`11/2003 Shewmake et al.
`11/2003 Mault et al.
`11/2003 Mault
`11/2003 Brown et al.
`12/2003 Brown
`3/2004 Giglio et al.
`7/2004 McGuire et al.
`7/2004 Kriger
`1/2005 Eldeiry
`2/2005 Mathur
`10/2005 Hodgdon
`10/2005 Hodgdon
`6/2006 Choi et al.
`2/2007 Friedrich et al.
`5/2007 Stivoric et al.
`1/2008 Tran
`7/2008 Gizewski
`11/2008 Stivoric et al.
`12/2009 Karkanias et al.
`3/2010 Naylor et al.
`1/2012 Bagan
`11/2012 Bessette
`
`8/2011 Bagan
`7,988,628 B2
`7/2012 Bessette et al.
`8,219,414 B2
`9,400,872 B2 * 7/2016 McGilvery
`
`2001/0032098 Al
`2001/0041845 Al
`2002/0011923 Al
`2002/0028995 Al
`2002/0049482 Al
`
`10/2001 Kulkarni
`11/2001 Kim
`1/2002 Cunningham et al.
`3/2002 Mault
`4/2002 Fabian et al.
`
`G06Q 50/22
`434/127
`
`OTHER PUBLICATIONS
`
`http://www.accufitness.com, accessed Apr.
`
`18, 2017.
`
`* cited by examiner
`
`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 3 of 25 PageID #: 14
`
`HARDWARE and SOFTWARE COMPONENTS for BEHAVIOR MANAGEMENT SYSTEM
`
`HARDWARE
`
`Internet-enabled
`devices
`(computers, smart
`phones, pdas, tvs)
`
`~
`\d
`
`Users I
`
`Professional and consumer
`biometric devices with
`bidirectional integration
`...
`•
`
`Network
`
`!
`
`Servers / Behavior Management Software
`
`3rd_Party professional and
`consumer biometric devices
`with unidirectional integration
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`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 4 of 25 PageID #: 15
`
`BEHAVIOR MANAGEMENT SYSTEM
`
`Behavior Management System
`
`Goal
`Desire
`
`I I
`
`Dynamic.
`Variabie,
`Filter-able
`Data
`Feedback
`
`9r::
`
`User
`Behavior
`Refine
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`
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`
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`
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`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 5 of 25 PageID #: 16
`
`DATA TYPES
`
`g
`
`User Generated Data
`
`• Biometric Data
`• Behavioral Data
`
`Biometric Hardware Device
`Generated Data
`
`• Biometric Data
`• Behavioral Data
`
`• Expression Data ~
`
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`
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`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 6 of 25 PageID #: 17
`
`DATA FLOW
`
`Internet-enabled
`devices
`(computers, smart
`phones, pdas, tvs)
`
`Users
`
`Q
`t
`
`Professional and consumer
`biometric devices with
`bidirectional integration
`
`3'd-Party professional and
`consumer biometric devices
`with unidirectional integration
`
`Assimilated
`3'0-Party
`Databases
`
`\
`
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`
`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 7 of 25 PageID #: 18
`
`U.S. Patent
`
`Sep.12,2017
`
`Sheet 5 of 15
`
`US 9,757,066 B2
`
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`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 8 of 25 PageID #: 19
`
`Your Results
`3/5/2009
`Date
`214.8 Pounds
`Weight
`45.4 %
`Body Fat
`1,805.6
`Metabolism
`35.7
`BMI
`Lean Mass 117.2 Pounds
`Fat Mass
`97.6 Pounds
`
`Choose One
`My Measurements
`
`I Weight vi
`
`Compare To:
`@ My Gender
`0 MyAge
`0 My Height
`0 My Body Type
`
`150 . . - - - - - - - - - - - - - - - - - - - ,
`Members: 6000
`Gender Female
`
`100
`
`50
`
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`
`Current Weight:
`Weight Position:
`
`214.8 lbs.
`97
`
`Median Weight:
`
`136Ibs.
`
`0 other members has the same value as you
`5,919 members have a lower value than you
`180 members have a higher value than you
`50% of members have a higher value and 50% of
`members have a lower value
`
`FIG.SA
`
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`
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`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 9 of 25 PageID #: 20
`
`WEB SCHEMATIC
`
`Q
`
`Quick Web Test
`or
`Device Test
`
`Quick Web Results
`or
`Device Results
`
`Join
`
`Getting Started
`Sequence
`
`User Record
`
`Profile Data
`Biometric Data
`Behavioral Data
`Expression Data
`Derivative Data
`System Data
`Process Data
`
`My Account
`
`Data Reservoir and Intelligence
`
`All User Records
`
`Assimilated Data
`
`All Profile Data
`All Biometric Data
`All Behavicral Data
`All Expression Data
`All Derivative Data
`All System Data
`All Process Data
`
`Additional Internal
`Process Data
`
`Additional Internal
`System Data
`
`Exercises
`
`Gear
`
`Tools
`
`Forums
`
`MySupport
`
`MyGraphs
`
`Feedback Interface
`
`Measurements
`Behavior
`
`Fig. 5
`
`Measurements
`
`Daily Log
`
`Meal Diary
`
`Schedule
`
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`
`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 10 of 25 PageID #: 21
`
`U.S. Patent
`
`Sep.12,2017
`
`Sheet 8 of 15
`
`US 9,757,066 B2
`
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`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 11 of 25 PageID #: 22
`
`Schedule Your Exercise
`
`Tip: Make A Realistic Commitment. How much exercise time can you commit to? It's okay to start slowly.
`Simple activities, like walking, count!
`National Institute of Health minimum recommendation: 30 minutes, three to four times per week
`
`Sunday
`
`Monday
`
`Tuesday Wednesday
`
`Thursday
`
`Friday
`
`Saturday
`
`0Rest
`OExercise
`
`ORest
`0Exercise
`
`l45min ~I 130 min ~I
`
`0Rest
`0Rest
`ORest
`0Exercise OExercise OExercise
`
`0Rest
`ORest
`0Exercise OExercise
`
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`
`Total minutes per week [ 125
`
`When done, click: [ Continue)
`
`FIG.6B
`
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`
`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 12 of 25 PageID #: 23
`
`U.S. Patent
`
`Sep.12,2017
`
`Sheet 10 of 15
`
`US 9,757,066 B2
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`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 13 of 25 PageID #: 24
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`U.S. Patent
`
`Sep.12,2017
`
`Sheet 11 of 15
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`US 9,757,066 B2
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`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 14 of 25 PageID #: 25
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`U.S. Patent
`
`Sep.12,2017
`
`Sheet 12 of 15
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`US 9,757,066 B2
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`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 15 of 25 PageID #: 26
`
`GETTING STARTED -ALERTS and REMINDERS
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`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 16 of 25 PageID #: 27
`
`DATA ORGANIZATION and ACCESS
`
`--
`
`User Record 1
`
`Measurement1
`M2
`I User Record 2
`M 3
`Mx
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`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 17 of 25 PageID #: 28
`
`How Am I Doing?
`
`Choose One
`My Measurements
`
`I Weight vi
`
`Compare To:
`[8J My Gender
`□ MyAge
`□ My Height
`□ My Body Type
`
`-
`
`Members: 9200
`Gender Male
`
`150
`
`100
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`50
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`Current Weight:
`Weight Position:
`
`186 lbs.
`62
`
`Median Weight:
`
`176 lbs.
`
`108 other members has the same value as you
`5,638 members have a lower value than you
`3,523 members have a higher value than you
`50% of members have a higher value and 50% of
`members have a lower value
`
`FIG. 8
`
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`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 18 of 25 PageID #: 29
`
`US 9,757,066 B2
`
`1
`METRICS ASSESSMENT SYSTEM FOR
`HEALTH, FITNESS AND LIFESTYLE
`BEHAVIORAL MANAGEMENT
`
`RELATED APPLICATIONS
`
`This present application is a continuation of U.S. non(cid:173)
`Provisional Application Ser. No. 15/199,513, filed Jun. 30,
`2016, which is a continuation of U.S. Non-Provisional
`Application Ser. No. 12/717,811, filed Mar. 4, 2010, now
`U.S. Pat. No. 9,400,872, issued Jul. 26, 2016, which claims
`priority to U.S. Provisional Application No. 61/157,856,
`filed Mar. 5, 2009. Each of these applications are incorpo(cid:173)
`rated by reference herein in their entireties.
`
`BACKGROUND OF THE INVENTION
`
`Field of the Invention
`The present invention relates generally to health, fitness,
`and lifestyle management, and more specifically to a soft(cid:173)
`ware and hardware system which enables effective lifestyle
`management by providing a dynamic assessment of a user's
`physical and behavioral metrics via a high feedback ratio
`interface.
`Description of the Related Art
`In the U.S., diet, exercise and personal health improve(cid:173)
`ment markets exceed $60 billion annually; yet, two thirds of
`adults are overweight. Links between obesity and numerous
`serious and fatal health conditions are well documented. 30
`Lost worker productivity and increased health care costs in
`America due to obesity exceed $100 billion annually. Being
`obese is unhealthy, expensive and diminishes one's quality
`of life. These sobering realities, as well as social and
`personal pressures, however, are apparently not effective
`enough drivers for most people to achieve a healthy weight.
`Obesity rates in America and around the developed world
`continue to rise at an alarming pace. A schism exists between
`what people want, or even need, and what they achieve.
`Although 95% of diets reportedly fail, the 5% who
`succeed at losing weight represent the entirety of the social,
`economic and physiological demographic spectrum. What,
`then, is the primary reason for this schism? The key differ(cid:173)
`entiator between those who succeed and fail is motivation
`and behavior management. Motivation fuels behavior and 45
`results follow behavior. The schism, then, is a failure of
`behavior management.
`A well-known key to weight control is a daily caloric
`balance-consume only as many calories in a day as are
`burned. That simple equation, however, and corresponding 50
`behavior is simply unattainable for many people. Why?
`Because the effort-to-reward mechanism is ineffective for
`too many people.
`Motivation is unsustainable in an ineffective effort-to-
`reward mechanism. An effective effort-to-reward mecha- 55
`nism can sustain motivation and enable effective behavior
`management. Effective effort-to-reward mechanisms meet
`necessary thresholds and balance of the following four
`criteria:
`1. Temporal-a reward must be timely enough to the 60
`effort to be an effective motivator. Optimally, the
`reward would occur during the effort or immediately
`following.
`2. Association-an effort and reward must be tangibly
`related to one another to be an effective motivator. 65
`Optimally, the effort and reward are viscerally related,
`an innately understood link.
`
`2
`3. Assimilation-a reward must have meaning and value
`to the subject to be an effective motivator.
`4. Ratio-a reward-to-effort ratio must meet a minimum
`threshold to be an effective motivator. The higher the
`ratio of reward to effort the more effective the motiva(cid:173)
`tion.
`It is important to note that 'necessary thresholds' vary
`from person to person. One size does not fit all. A system or
`method must be flexible to allow individual discovery of
`10 their own effective motivational threshold. In a fully realized
`healthy lifestyle,
`'exercise' and
`'eating right' become
`rewards themselves.
`Existing methods or systems to heighten people's moti-
`15 vation and enable behavior management to achieve health,
`fitness and lifestyle goals include: weight-loss counseling,
`pre-prepared and portioned meals, peer-to-peer support
`groups, fitness groups and clubs, health challenges, hypnosis
`and many others. Many of these methods and systems have
`20 been in existence for years, even decades, yet obesity rates
`have nearly doubled in the past thirty years. For many
`people, current methods and systems fail to satisfy all four
`requirements of an effective effort-to-reward mechanism.
`Most lifestyle goals cannot be achieved in a single action;
`25 they are a process, achieved over time. If the action and
`behavior itself is not a reward mechanism for the individual,
`then additional feedback and reward mechanisms are nee-
`essary.
`Prior art methods or systems that attempt temporally
`effective reward mechanisms include data tracking websites
`or websites associated with personal biometric devices. The
`data feedback on such sites is often focused on a single
`metric, which is narrow and minimally informative.
`Weight-loss support group sites have a marginally better
`35 feedback ratio for posted comments or messages; users can
`receive several replies for each message. The relationship
`between the feedback/reward and the user's overall goal in
`these cases, however, is marginalized. If the user's overall
`goal is to lose weight, for example, how direct of a reward
`40 to that effort is this feedback? The reward of support
`messages is more closely related to the behavior of message
`exchanging itself, and only tangentially related to losing
`weight. It is a step removed from the efforts and behaviors
`of actually losing weight.
`A user needs a personal connection or meaning to the
`feedback/reward to be effective. Too often, user profiling is
`not sufficiently varied or personalized. Meaningful feed(cid:173)
`back, therefore, is limited and contributes to low effort-to(cid:173)
`reward feedback ratios.
`In existing systems, the desired goal is often a number, a
`fixed measurement, of what is considered healthy for some(cid:173)
`one with the user's attributes. This number, this goal mea(cid:173)
`surement, is historically a very poor motivator. People have
`been told what they are supposed to weigh many times
`already. Familiarity with a number is not the same as a
`relationship or meaning.
`
`SUMMARY OF THE INVENTION
`
`What is needed is a new set of assessment metrics that are
`fresh, motivating, and meaningful. The present invention
`provides methods and systems of motivation and behavior
`management that provides a user with a novel assessment
`with an effort-to-reward mechanism that is (1) temporal, (2)
`tangible, (3) personally meaningful, and (4) has a much
`greater feedback ratio that is far more effective than existing
`weight-loss, fitness and lifestyle programs.
`
`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 19 of 25 PageID #: 30
`
`US 9,757,066 B2
`
`3
`To enable effective health, fitness and lifestyle behavior
`management, a software and hardware system has been
`developed that provides immediate, meaningful and engag(cid:173)
`ing feedback for physical and behavioral metrics by provid(cid:173)
`ing a dynamic assessment of these metrics via a high 5
`feedback ratio interface. The system simultaneously meets
`the requirements of all four effort-to-reward feedback
`mechanisms-temporal, assocrnt10n,
`assimilation, and
`ratio----of an effective behavior management tool.
`The hardware and software system is designed to opti- 10
`mize data collection, organization and display. Hardware
`components include integrated biometric devices, such as
`scales, that make data collection automatic and comprehen(cid:173)
`sive. Data is stored and organized on computer servers. User 15
`assessments and data display are conveniently accessible
`from Internet-enabled devices.
`A powerful system of metrics and filters allows for a
`simultaneously broad and deep user assessment spectrum.
`Motivational and obstacle profile typing provide a greater
`variety of data nodes in member records creating flexibility.
`New assessment metrics, including positions and rankings,
`utilize dynamic reference data sets that can be filtered to
`more and more closely resemble any particular user. User
`interactivity with the data enriches the user experience and
`provides more meaningful data feedback, and is a key to the
`effort-to-reward mechanism. Feedback based on cross ref(cid:173)
`erencing various metrics simultaneously can assist in users
`refining their behaviors to be more effective.
`Users complete their profile by defining their goal, exer- 30
`cise and nutrition schedule, motivational and obstacle data,
`and other system preferences. Each of these data points is an
`additional data node for organizing feedback. Upon com(cid:173)
`pleting their profile, users record their activities on a daily
`basis and their physical measurements periodically. From
`time to time, users may participate in health and fitness
`challenges, competitions or other data organizational
`schemes. Physical measurements may be recorded manually
`or automatically via an integrated biometric device. Imme(cid:173)
`diately following data entry, users access one of several
`dynamic high feedback ratio interfaces. These interfaces
`allow the user to obtain an assessment of physical metrics,
`such as weight and body fat percentage, or behavioral
`metrics, such as login frequency and mood. A variety of
`metric assessments are available. Assessment feedback is
`dynamic, in that, the active reference data set changes with
`overall system usage in nearly live terms.
`Rankings and position assessments offer viscerally under(cid:173)
`stood answers to "how am I doing?" questions. Via various
`screens, users can be ranked or positioned, on a percentile 50
`scale of 1-1 00, against other profiles in the active reference
`data set. The active reference data set is flexible; it can be
`filtered at the user's whim in real time.
`The dynamic and flexible ranking and position assess(cid:173)
`ments features satisfy the criteria for an effective behavior 55
`management system:
`Temporal Assessment feedback rewards immediately fol(cid:173)
`low user data entry.
`Association The behavior of entering data and data
`assessment feedback are directly related. Users, in 60
`effect, take a "BodySpex measurement" to find out how
`they're doing.
`Assimilation Ranking and positions on a scale of I-100
`are innately easy to grasp. Filtering allows for mean(cid:173)
`ingful reference data sets.
`Ratio Multiple metrics and filters options provide users
`with a feedback interface that is very high-ratio.
`
`4
`This system is a positive feedback loop. The very act of
`accessing the database to see a user's rank and/or position
`adds more data to the database. A user enters his or her data
`to find out where he/she ranks, thus increasing the data pool
`for the next user. The increased data pool is more informa(cid:173)
`tive, more valuable, and encourages the next user to see
`where he or she ranks.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`The present invention is illustrated by way of example
`and not limited m the accompanying figures in which:
`FIG. lA shows an illustrative conceptual diagram of a
`behavior management system. Between a user's goal desire
`and goal achievement is the user's behaviors over time. A
`behavior management system utilizes software to define the
`goal and metrics to determine progress, to collect user data
`of these metrics including behavioral metrics, and to provide
`a meaningful assessment, so that the user may refine and
`20 improve behaviors. The cycle continues until the goal is
`achieved.
`FIG. 1 shows a block diagram of components of a
`hardware and software behavioral management system.
`Users are connected to the behavior management software
`25 via hardware and a network. Hardware includes Internet-
`enabled devices, professional and consumer biometric
`devices with bidirectional integration and third party pro(cid:173)
`fessional and consumer biometric devices with unidirec-
`tional integration.
`FIG. 2 shows a flow diagram of data types in a hardware
`and software behavioral management system. User gener(cid:173)
`ated data, biometric hardware device generated data, and
`software generated data flow over a network.
`FIG. 3 shows a flow diagram of data between various
`35 components of a hardware and software behavioral man(cid:173)
`agement system. Data flows from and to users via Internet(cid:173)
`enabled devices, professional and consumer biometric
`devices with bidirectional integration and third party pro(cid:173)
`fessional and consumer biometric devices with unidirec-
`40 tional integration. Each of these data streams connects with
`the BodySpex servers via a network. Additional third party
`assimilated data flows to the servers directly or via a
`network.
`FIG. 4 shows a block diagram of the System Architecture,
`45 which illustrates the relationships between users, biometric
`devices, the website, web services, and the database.
`FIG. SA shows an exemplary webpage where a user is
`presented with data feedback in the form of a Results Page.
`FIG. 5 shows a schematic and data flowchart for the
`website. Users join, and then set up their user record,
`optionally by completing a getting started sequence. User
`records are maintained and updated via various data entry
`screens and functions. All user record data is stored in an
`intelligent reservoir on the servers, where it is organized and
`related with other data, such as, assimilated data, internal
`process and system data, exercise, gear, tools, and forum
`data. Data is displayed for the user via their MySpex page,
`support features and high feedback ratio interfaces.
`FIG. 6A shows an exemplary webpage for a user defining
`their goal in the getting started sequence. Users define their
`goal, assign their metric and target measure measurement.
`This goal is related to personal goal reasons and goal
`rewards creating additional data nodes for feedback.
`FIG. 6B shows an exemplary webpage for a user sched-
`65 uling their exercise in the getting started sequence. Users
`assign each day of the week for rest or exercise. For exercise
`days, the user declares how many minutes he/she plans to
`
`

`

`Case 2:20-cv-00106-JRG Document 1-1 Filed 04/14/20 Page 20 of 25 PageID #: 31
`
`US 9,757,066 B2
`
`5
`engage in some form of exercise. In some embodiments, the
`user can select from a menu of specific exercises or fully
`defined exercise plans. These are additional data nodes for
`feedback.
`FIG. 6C shows an exemplary webpage for a user defining
`their nutritional and other behavioral tracking in the getting
`started sequence. Users select any number of additional
`behaviors to track. These are additional data nodes for
`feedback.
`FIG. 6D shows an exemplary webpage for a user com(cid:173)
`pleting their motivational profile in the getting started
`sequence. A user is presented with four questions with an A
`or B answer which most closely reflects their motivational
`profile. This feature creates sixteen distinct motivational
`profiles and each user is flagged for one and only one. This
`is an additional data node for feedback.
`FIG. 6E shows an exemplary webpage for a user com(cid:173)
`pleting their obstacle profile in the getting started sequence.
`A user is presented with a list of obstacle statements which
`are selected as applicable to reflect the user's historical
`obstacles to achieving their goal. This feature is organized to
`create sixteen distinct obstacle profiles and each user is
`flagged for one and only one. This is an additional data node
`for feedback.
`FIG. 6F shows an exemplary webpage for a user com(cid:173)
`pleting their alert and reminder settings in the getting started
`sequence. Users select under what circumstances they want
`system alert and reminder prompts via email. In addition to
`system logic, selections by the user are additional data nodes
`for feedback.
`FIG. 7 shows a diagram of how user data is accessible and
`flexible via the interactive chart. User records include all
`personal physical and behavioral measurements as well as
`other data typing used for filters. All user records are stored
`and organized together and can be accessed via the feedback
`interfaces to find measurement data counts given any com(cid:173)
`bination of filters.
`FIG. 8 shows an exemplary webpage of the high feedback
`ratio interface. Users select a metric, then filters as desired.
`A chart or graph or other data display type is automatically
`generated. In this case, a histogram chart of male weight is
`displayed with a member count on the 'y' axis and number
`of pounds on the 'x' axis. User rank or position, as appli(cid:173)
`cable, is displayed along with other pertinent information
`about the active reference data set.
`
`DETAILED DESCRIPTION OF THE
`PREFERRED EMBODIMENT
`
`FIG. lA illustrates the conceptual architecture of an
`effective hardware and software behavior management sys(cid:173)
`tem. Between a user's goal desire and goal achievement is
`the user's behavior cycle. User behaviors are parsed into a
`set of metrics that can be measured to determine progress. 55
`User measurements, including both physical and behavioral
`data, with respect to these metrics are stored on servers. Data
`can be manually entered, captured via integrated biometric
`hardware devices or generated by software system pro(cid:173)
`cesses. User data is organized to enable the display of
`meaningful and engaging assessment feedback. The present
`effective behavior management system provides assessment
`feedback that meets the