Adaptive analytical behavioral and health assistant system and related method of use

• US 10,152,675 B2
• Filed: 05/18/2015
• Issued: 12/11/2018
• Est. Priority Date: 03/24/2011
• Status: Active Grant

• Current Assignee: WellDoc, Inc
• Original Assignee: WellDoc, Inc
• Inventors: Sudharsan, Bharath
• Primary Examiner(s): Chen, Alan
• Application Number:
  US14/714,828
• Publication Number:
  US 20150248533A1
• Time in Patent Office: 1,303 Days
• Field of Search: None
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

This present disclosure relates to systems and methods for providing an Adaptive Analytical Behavioral and Health Assistant. These systems and methods may include collecting one or more of patient behavior information, clinical information, or personal information; learning one or more patterns that cause an event based on the collected information and one or more pattern recognition algorithms; identifying one or more interventions to prevent the event from occurring or to facilitate the event based on the learned patterns; preparing a plan based on the collected information and the identified interventions; and/or presenting the plan to a user or executing the plan.

Claims

1. A computer-implemented method for managing health of a user, the method comprising:

collecting, by one or more processors, information relating to the user;

learning, by the one or more processors, one or more patterns that cause an event based on the collected information and one or more algorithms;

identifying, based on the learned patterns, one or more actions to prevent the event from occurring or to facilitate the event;

preparing a plan based on the collected information and the identified one or more actions;

presenting the plan to the user or executing the plan;

electronically requesting feedback from the user relating the user'"'"'s subjective assessment of the plan;

electronically receiving the feedback relating to the plan from the user in response to the request;

automatically revising the plan based on the feedback;

wherein automatically revising the plan includes;

identifying, based on the feedback from the user, one or more actions to prevent the event from occurring or to facilitate the event;

presenting the one or more actions to the user;

after presenting the one or more actions to the user, determining that the user'"'"'s subjective assessment is inaccurate;

after determining the user'"'"'s subjective assessment is inaccurate, reducing a weight assigned to the user'"'"'s subjective assessment when identifying the one or more actions to prevent the event from occurring or to facilitate the event;

after determining the user'"'"'s subjective assessment is inaccurate, increasing a weight assigned to the learned patterns when identifying the one or more actions to prevent the event from occurring or to facilitate the event; and

identifying, based on the reduced weight assigned to the user'"'"'s subjective assessment is inaccurate and based on the increased weight assigned to the learned patterns, one or more actions to prevent the event from occurring or to facilitate the event.

2. The computer-implemented method of claim 1, wherein:

the feedback also includes one or more user behaviors that occur after the plan is prepared or presented to the user; and

the revised plan includes one or more additional actions automatically selected based on the feedback.

3. The computer-implemented method of claim 1, wherein the feedback also includes a type of medication taken by the user, and a time at which the medication was taken.

4. The computer-implemented method of claim 1, wherein the feedback also includes information relating to food consumed by the user.

5. The computer-implemented method of claim 1, wherein the feedback also includes information relating to exercise performed by the user.

6. The computer-implemented method of claim 1, wherein the event is a blood glucose level of the user that is below a normal range.

7. A computer-implemented method for managing health of a user, the method comprising:

analyzing, using at least one processor, user specific data relating to a user care plan, and learning one or more patterns that cause an event based on the user specific data and one or more algorithms;

electronically requesting feedback from the user relating the user'"'"'s subjective assessment of the plan;

electronically receiving the feedback from the user in response to the request;

determining one or more actions based on the learned patterns and the user'"'"'s subjective assessment;

automatically preparing and presenting a revised user care plan based on the user specific data and the identified one or more actions;

determining a speed of an electronic device associated with the user; and

presenting the revised patient care plan based on the speed of the electronic device, wherein presenting the revised patient care plan based on the speed of the electronic device includes selecting a type of electronic data to present based on a processor speed of the electronic device and a speed of an electronic network to which the electronic device connects.

8. The computer-implemented method of claim 7, wherein the feedback includes data manually entered into the electronic device.

9. The computer-implemented method of claim 7, wherein the user specific data comprises a blood glucose level received from a blood glucose monitor.

10. The computer-implemented method of claim 7, wherein the user specific data comprises user interaction data.

11. The computer-implemented method of claim 7, wherein the revised user care plan is presented to the user on multiple electronic devices.

12. The computer-implemented method of claim 7, wherein the revised user care plan comprises electronic content, wherein the electronic content includes a video tutorial.

13. The computer-implemented method of claim 7, further including automatically making one or more inferences based on machine learning using the user specific data, wherein automatically preparing and presenting the revised user care plan also is based on the one or more inferences.

14. The computer-implemented method of claim 7, further including transmitting an alert related to a non-beneficial action of the user.

15. A computer-implemented method for managing health of a user, the method comprising:

collecting, by one or more processors, information relating to the user;

learning, by the one or more processors, one or more patterns that cause an event based on the collected information and one or more algorithms;

identifying, based on the learned patterns, one or more actions to prevent the event from occurring or to facilitate the event;

preparing a plan based on the collected information and the identified one or more actions;

presenting the plan to the user or executing the plan;

electronically requesting feedback from the user relating the user'"'"'s subjective assessment of a manner in which the plan was presented to the user;

electronically receiving the feedback from the user in response to the request, wherein the user manually enters the feedback into a computing device, and the feedback includes indicating whether the user prefers text-based information or visual-based information, and the feedback also includes indicating a preferred frequency for content delivery relating to the plan;

automatically revising the plan based on the feedback, wherein automatically revising the plan includes;

identifying, based on the feedback from the user and the learned patterns, one or more actions to prevent the event from occurring or to facilitate the event;

presenting the one or more actions to the user;

after presenting the one or more actions to the user, determining that the user'"'"'s subjective assessment is inaccurate;

after determining the user'"'"'s subjective assessment is inaccurate, reducing a weight assigned to the user'"'"'s subjective assessment when identifying the one or more actions to prevent the event from occurring or to facilitate the event;

after determining the user'"'"'s subjective assessment is inaccurate, increasing a weight assigned to the learned patterns when identifying the one or more actions to prevent the event from occurring or to facilitate the event; and

identifying, based on the reduced weight assigned to the user'"'"'s subjective assessment is inaccurate and based on the increased weight assigned to the learned patterns, one or more actions to prevent the event from occurring or to facilitate the event.

16. The computer-implemented method of claim 15, wherein the one or more actions includes each of:

1) changing a diet of the user;

2) ordering medication;

3) contacting a doctor;

4) changing an exercise routine of the user; and

5) indicating that the user should rest.