IP Library › Granted Patent US 12,342,240

Granted Patent B2

US 12,342,240 · App. 17/861,559 · Granted Jun 24, 2025

Systems and methods for monitoring for and lowering the risk of addiction-related or restriction violation-related behavior(s)

Inventor: David H. Williams (Kirkwood, MO)

H04W4/021 A61B5/0022 A61B5/4842 A61B5/6802 A61B5/7264 A61B5/747 A63F9/12 G06F21/36 G06Q10/0635 G06Q20/3224 G06Q20/401 G06Q20/4014 G06Q20/4016 G07F17/3237 G16H40/67 G16H50/30 H04L63/107 H04L63/20 H04L67/12 H04W4/029 H04W12/08 G06F2221/2111 H04W12/06

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Quick Facts

Patent No.: US 12,342,240
App. No.: 17/861,559
Granted: Jun 24, 2025
Kind: B2

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Abstract

Exemplary embodiments are disclosed of systems and methods for monitoring for and lowering the risk of addiction-related or restriction violation-related behavior(s).

Claims (107)

1. A system comprising a plurality of devices, sensors, and communication network(s), the system configured to:

determine, through a plurality of measurements/readings taken by the plurality of devices, sensors, and communication network(s), behavior(s) of at least one person and

(a) context(s) associated with the behavior(s) of the at least one person; or

(b) location and the context(s) associated with the behavior(s) of the at least one person;

analyze the measurements/readings, the behavior(s) of the at least one person, and (a) the context(s) associated with the behavior(s) of the at least one person or (b) the location and the context(s) associated with the behavior(s) of the at least one person at the location, that are associated with at least one related trigger that is related to either or both of an addiction-related trigger and a restriction violation-related trigger, to thereby determine a risk of an addiction-related or restriction violation-related behavior(s) of the at least one person relative to at least one trigger threshold(s) or trend(s);

facilitate one or more actions to lower the risk of the addiction-related or restriction violation-related behavior(s) associated with the at least one related trigger from reaching or exceeding the trigger threshold(s) associated with the addiction-related or restriction violation-related behavior(s) before the addiction-related or restriction violation-related behavior(s) occurs; and

monitor result(s) of the one or more actions, learn effectiveness of risk lowering action(s) from the monitored result(s), and determine system modification(s), if any, related to the at least one person's likelihood or relapse and/or occurrence of the addiction-related or restriction violation-related behavior(s), the effectiveness of the risk lowering action(s), and types and frequency of the measurements/readings taken by the plurality of devices, sensors, and communication network(s);

wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person, skin and/or body temperature of the at least one person, and ambient temperature; and

the system is configured to determine that an Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person, the skin and/or body temperature of the at least one person, and the ambient temperature.

2. The system of claim 1 , wherein the system is configured to utilize artificial intelligence or machine learning to determine system modification(s), if any, to profile parameter(s) of the at least one person, risk determination algorithm(s) and/or measurements/readings taken by the plurality of devices, sensors, and communications network(s) relative to the at least one related trigger and/or the addiction-related or restriction violation-related behavior(s) of the at least one person.

3. The system of claim 1 , wherein the system is configured to determine whether any other trigger(s) related to the Anger trigger for the at least one person is active, in danger of becoming active, or imminent, including two or more of a Frustration trigger, a Job trigger, a Personal Relationship trigger, a Stress trigger, a Despair trigger, a Self-Loathing trigger, a Resentment trigger, an Information Overload/Snowball Effect trigger, and/or a Yelling trigger.

4. The system of claim 1 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring proximity of the at least one person to one or more other persons; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person, the skin and/or body temperature of the at least one person referenced to the ambient temperature, and proximity of the at least one person to the one or more other persons.

5. The system of claim 1 , wherein the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person and a change in the skin and/or body temperature of the at least one person referenced to the ambient temperature.

6. The system of claim 1 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring ambient noise level; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person referenced to the ambient noise level and/or a change in the skin and/or in body temperature of the at least one person referenced to the ambient temperature.

7. The system of claim 1 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring blood pressure of the at least one person and ambient noise level; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person referenced to the ambient noise level, a change in the skin and/or body temperature of the at least one person referenced to the ambient temperature, and/or a change in blood pressure of the at least one person.

8. The system of claim 1 , wherein the system is configured to utilize artificial intelligence or machine learning to learn from the at least one person's addiction-related and/or restriction violation-related behavior(s) and response(s) to behavioral modification action(s), and to refine system parameter(s), if any, related to the at least one person's likelihood or relapse and/or occurrence of the addiction-related or restriction violation-related behavior(s), the effectiveness of the risk lowering action(s), and types and frequency of the measurements/readings taken by the plurality of devices, sensors, and communication network(s).

9. The system of claim 1 , wherein the system is configured to utilize artificial intelligence or machine learning to determine:

which of the plurality of devices, sensors, and communication network(s) are used;

types and frequency of the measurements/readings taken by the plurality of devices, sensors, and communication network(s); and

which of the system's algorithm(s), digital agent(s), and engine(s) are used.

10. The system of claim 1 , wherein the system includes a learning engine configured to utilize artificial intelligence or machine learning to learn from the at least one person's behavior and response(s) to behavioral modification action(s) and to refine the system's algorithm(s), and process(es) related to the at least one person's likelihood or relapse and/or occurrence of the addiction-related or restriction violation-related behavior(s), the effectiveness of the risk lowering action(s), and types and frequency of the measurements/readings taken by the plurality of devices, sensors, and communication network(s).

11. The system of claim 1 , wherein the system includes a learning engine configured to utilize artificial intelligence or machine learning to analyze the measurements/readings, the behavior(s) of the at least one person, and (a) the context(s) associated with the behavior(s) of the at least one person or (b) the location and the context(s) associated with the behavior(s) of the at least one person at the location, that are associated with at least one related trigger that is related to either or both of an addiction-related trigger and a restriction violation-related trigger, to thereby determine a risk of an addiction-related or restriction violation-related behavior(s) of the at least one person relative to at least one trigger threshold(s) or trend(s).

12. The system of claim 1 , wherein the system is configured to utilize a prediction algorithm(s) or a scoring formula(s) for determining a current or trending degree of risk of the addiction-related or restriction violation-related behavior(s) of the at least one person.

13. The system of claim 1 , wherein the system is configured to:

determine whether (a) the context(s) associated with the behavior(s) of the at least one person corresponds to a high-risk context or (b) the location and the context(s) associated with the behavior(s) of the at least one person at the location correspond to a high-risk location and context

identify one or more of available support resource(s) and interface(s) for the at least one person to mitigate the risk of the addiction-related or restriction violation-related behavior(s) of the at least one person;

select one or more of the identified available support resource(s) and interface(s) for the at least one person; and

implement the selected available support resource(s) and interface(s) for the at least one person if the (a) context(s) associated with the behavior(s) of the at least one person or (b) the location and the context(s) associated with the behavior(s) of the at least one person at the location correspond to a trending risk of the addiction-related or restriction violation-related behavior(s) of the at least one person.

14. The system of claim 13 , wherein:

the interface(s) includes at least one interface(s) configured to enable interaction between the at least one person and a support network or third party (ies); and

the support resource(s) include at least one member of the at least one person's support network including a sponsor, a family member, or a friend.

15. The system of claim 1 , wherein the system is configured to determine whether any other trigger(s) related to the Anger trigger for the at least one person is active, in danger of becoming active, or imminent, including one or more of Anxiety, Boredom, Change, Conflict, Depression, Disorder, Envy, Desire to Escape, Excitement, Extreme Emotions, Fear, Frustration, Guilt, Health problems, Holidays, Hunger, Insomnia, Job issues, Kids/Children, Loneliness, Media marketing, Mid-Life Crisis, Money problems, Music, Noise, Overconfidence, Peer Pressure, Power, Powerlessness, Proximity to an Addictive Substance, Fear of Quitting, Relationships, Relatives, Reminders, Sex, Change of Seasons, Smell, Social Situations, Stress, Taste, Times of Day, Being Tired, Feeling Not Fun, Unhappy, Feeling Victimized, Weather, Yelling, and Zeal.

16. The system of claim 1 , wherein the system is configured to utilize artificial intelligence or machine learning to learn from the at least one person's behavior and response(s) to behavioral modification action(s) and modify the system including modifications related to encouragement or avoidance of (a) the context(s) associated with the behavior(s) of the at least one person or (b) the location and the context(s) associated with the behavior(s) of the at least one person at the location, who and/or what support resource(s) and interface(s) are utilized and when.

17. The system of claim 1 , wherein the system is configured to utilize artificial intelligence or machine learning to learn from the at least one person's behavior and response(s) to behavioral modification action(s) and modify the system including modifications to the types and frequency of the measurements/readings taken by the plurality of devices, sensors, and communication network(s) relating to:

noise types, levels monitored, frequency of monitoring of noise types and levels, changes to yelling, speech patterns, word usage, speech, yelling volume and speech clarity, changes in the skin and/or body temperature of the at least one person; and

type(s), level(s), threshold(s), trend(s) parameter(s) and frequency of monitoring by the plurality of devices, sensors, and communication network(s).

18. The system of claim 1 , wherein the system is configured to utilize artificial intelligence or machine learning to learn from the at least one person's behavior and response(s) to behavioral modification action(s) and modify the system including modifications to the usage(s), value(s), threshold(s), range(s), trend(s) parameter(s), and weight(s) of the types and frequency of the measurements/readings taken by the plurality of devices, sensors, and communication network(s) that are utilized in trigger risk prediction algorithm(s) of the system.

19. The system of claim 1 , wherein the system is configured such that in response to detection of the Anger trigger and an unsuccessful call to a first family member of the at least one person to alleviate the Anger trigger, the system is configured to use artificial intelligence or machine learning to determine a second family member to call in an attempt to alleviate the Anger trigger of the at least one person.

20. A system comprising a plurality of devices, sensors, and communication network(s), the system configured to:

determine, through a plurality of measurements/readings taken by the plurality of devices, sensors, and communication network(s), behavior(s) of at least one person and

(a) context(s) associated with the behavior(s) of the at least one person; or

(b) location and the context(s) associated with the behavior(s) of the at least one person;

wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring skin and/or body temperature of the at least one person and ambient temperature; and

21. The system of claim 20 , wherein the system is configured to utilize artificial intelligence or machine learning to determine system modification(s), if any, to profile parameter(s) of the at least one person, risk determination algorithm(s) and/or measurements/readings taken by the plurality of devices, sensors, and communications network(s) relative to the at least one related trigger and/or the addiction-related or restriction violation-related behavior(s) of the at least one person.

22. The system of claim 20 , wherein the system is configured to determine whether any other trigger(s) related to the Anger trigger for the at least one person is active, in danger of becoming active, or imminent, including two or more of a Frustration trigger, a Job trigger, a Personal Relationship trigger, a Stress trigger, a Despair trigger, a Self-Loathing trigger, a Resentment trigger, an Information Overload/Snowball Effect trigger, and/or a Yelling trigger.

23. The system of claim 20 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring ambient noise level; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the skin and/or body temperature of the at least one person referenced to the ambient temperature and a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person referenced to the ambient noise level.

24. The system of claim 20 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring proximity of the at least one person to one or more other persons; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the skin and/or body temperature of the at least one person referenced to the ambient temperature and proximity of the at least one person to the one or more other persons.

25. The system of claim 20 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring blood pressure of the at least one person; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the skin and/or body temperature of the at least one person referenced to the ambient temperature and a change in blood pressure of the at least one person.

26. A system comprising a plurality of devices, sensors, and communication network(s), the system configured to:

determine, through a plurality of measurements/readings taken by the plurality of devices, sensors, and communication network(s), behavior(s) of at least one person and

(a) context(s) associated with the behavior(s) of the at least one person; or

(b) location and the context(s) associated with the behavior(s) of the at least one person;

wherein:

the system is configured to determine that an Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person referenced to the ambient noise level.

27. The system of claim 26 , wherein the system is configured to utilize artificial intelligence or machine learning to determine system modification(s), if any, to profile parameter(s) of the at least one person, risk determination algorithm(s) and/or measurements/readings taken by the plurality of devices, sensors, and communications network(s) relative to the at least one related trigger and/or the addiction-related or restriction violation-related behavior(s) of the at least one person.

28. The system of claim 26 , wherein the system is configured to determine whether any other trigger(s) related to the Anger trigger for the at least one person is active, in danger of becoming active, or imminent, including two or more of a Frustration trigger, a Job trigger, a Personal Relationship trigger, a Stress trigger, a Despair trigger, a Self-Loathing trigger, a Resentment trigger, an Information Overload/Snowball Effect trigger, and/or a Yelling trigger.

29. The system of claim 26 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring skin and/or body temperature of the at least one person and ambient temperature; and

30. The system of claim 26 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring proximity of the at least one person to one or more other persons; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person referenced to the ambient noise level and proximity of the at least one person to the one or more other persons.

31. The system of claim 26 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring blood pressure of the at least one person; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person referenced to the ambient noise level and a change in blood pressure of the at least one person.

32. A system comprising a plurality of devices, sensors, and communication network(s) configured for monitoring noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of at least one person, skin and/or body temperature of the at least one person, and ambient temperature, wherein the system is configured to determine, through a plurality of measurements/readings taken by the plurality of devices, sensors, and communication network(s), that an Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person, the skin and/or body temperature of the at least one person, and the ambient temperature, and wherein the system is further configured to:

facilitate one or more actions to lower the risk of the Anger trigger from reaching or exceeding an Anger trigger threshold(s); and

monitor result(s) of the one or more actions, learn effectiveness of risk lowering action(s) from the monitored result(s), and determine system modification(s), if any, related to the at least one person's likelihood or relapse and/or occurrence of an undesirable behavior(s), the effectiveness of the risk lowering action(s), and types and frequency of the measurements/readings taken by the plurality of devices, sensors, and communication network(s).

33. The system of claim 32 , wherein the system is configured to determine, through the plurality of measurements/readings taken by the plurality of devices, sensors, and communication network(s), behavior(s) of at least one person and

(a) context(s) associated with the behavior(s) of the at least one person; or

(b) location and the context(s) associated with the behavior(s) of the at least one person.

34. The system of claim 33 , wherein the system is configured to analyze the measurements/readings, the behavior(s) of the at least one person, and (a) the context(s) associated with the behavior(s) of the at least one person or (b) the location and the context(s) associated with the behavior(s) of the at least one person at the location, that are associated with at least one related trigger that is related to the Anger trigger, to thereby determine a risk of the undesirable behavior of the at least one person relative to at least one trigger threshold(s) or trend(s).

35. The system of claim 34 , wherein the system is configured to facilitate one or more actions to lower the risk of the undesirable behavior(s) associated with the at least one related trigger a trigger(s) from reaching or exceeding the trigger threshold(s) associated with the undesirable behavior(s) before the undesirable behavior(s) occurs.

36. The system of claim 35 , wherein the system is configured to utilize artificial intelligence or machine learning to determine system modification(s), if any, to profile parameter(s) of the at least one person, risk determination algorithm(s) and/or measurements/readings taken by the plurality of devices, sensors, and communications network(s) relative to the at least one related trigger and/or the undesirable behavior(s) of the at least one person.

37. The system of claim 32 , wherein the system is configured to determine whether any other trigger(s) related to the Anger trigger for the at least one person is active, in danger of becoming active, or imminent, including two or more of a Frustration trigger, a Job trigger, a Personal Relationship trigger, a Stress trigger, a Despair trigger, a Self-Loathing trigger, a Resentment trigger, an Information Overload/Snowball Effect trigger, and/or a Yelling trigger.

38. The system of claim 32 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring proximity of the at least one person to one or more other persons; and

39. The system of claim 32 , wherein the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person and a change in the skin and/or body temperature of the at least one person referenced to the ambient temperature.

40. The system of claim 32 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring ambient noise level; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person referenced to the ambient noise level and/or a change in the skin and/or in body temperature of the at least one person referenced to the ambient temperature.

41. The system of claim 32 , wherein:

the plurality of devices, sensors, and communication network(s) are configured for monitoring blood pressure of the at least one person and ambient noise level; and

the system is configured to determine that the Anger trigger for the at least one person is active, in danger of becoming active, or imminent based on the measurements/readings of a change in the noise type(s) and/or level(s), yelling, speech pattern(s), word usage, speech volume, and/or clarity of speech of the at least one person referenced to the ambient noise level, a change in the skin and/or body temperature of the at least one person referenced to the ambient temperature, and/or a change in blood pressure of the at least one person.

Assignments (1)

ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 11, 2022

From: WILLIAMS, DAVID H.

To: CONQUER YOUR ADDICTION LLC

Reel/Frame 060477/0208 →

Continuity (5)

Continuation In Part 16700601 · Dec 2, 2019

Continuation 15840775 · Dec 13, 2017

Provisional Application 62480206 · Mar 31, 2017

Provisional Application 62435042 · Dec 15, 2016

Related Publication 20220353632A1 · Nov 3, 2022

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