Adaptive pain management and reduction based on monitoring user conditions

Patent metadata

Field	Value
Publication number	US-11929177-B2
Application number	US-202117224746-A
Country	US
Kind code	B2
Filing date	Apr 7, 2021
Priority date	May 22, 2018
Publication date	Mar 12, 2024
Grant date	Mar 12, 2024

Abstract

Techniques regarding pain treatment are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can include: a data collection component that can determine at least one parameter associated with a pain perception of a subject, a computing component that can determine a relationship between the pain perception and the at least one parameter using artificial intelligence, and can determine a treatment for the subject based on the relationship; and a treatment component that can cause a device associated with the subject to apply at least a portion of the treatment.

First claim

What is claimed is:

1. A system, comprising:
a memory that stores computer executable components;
a processor, operably coupled to the memory, and that executes the computer executable components stored in the memory, wherein the computer executable components comprise:
a data collection component that determines, using one or more sensors, parameter data associated with a subject over a period of time, wherein the parameter data comprises psychological data comprising at least one psychological parameter associated with the subject, physiological data comprising at least one physiological parameter associated with the subject, behavior data comprising activities performed by the subject, treatment data comprising a group of treatments applied to the subject, and timing data comprising times associated with the parameter data;
a computing component that, using a machine learning model iteratively during the period of time:
determines pain perception data representative of pain perception of the subject at the times based on the psychological data and the physiological data,
learns relationships between the psychological data, the physiological data, the behavior data, the treatment data, the pain perception data, and the timing data, and
generates, based on the learned relationships, an optimal treatment comprising one or more combinations of treatments from the group of treatments, and timings for administration of the one or more combinations of treatments to reduce the pain perception of the subject; and

a treatment component that controls a device associated with the subject to administer at least a portion of the optimal treatment to the subject.

2. The system of claim 1 , wherein the parameter data further comprises environmental data comprising at least one environmental parameter associated with the subject.

3. The system of claim 2 where the learned relationships are further based on the environmental data.

4. The system of claim 1 , wherein the group of treatments comprise at least one of a medication, a wearable device, or a procedure.

5. The system of claim 1 , further comprising a communication component that:
presents the optimal treatment as a suggestion to the subject via an interface that enables the subject to evaluate an effectiveness of the optimal treatment, and
receives input from the subject indicating whether the subject approves the optimal treatment.

6. The system of claim 1 , wherein the treatment component comprises causes the device associated with the subject to apply at least the portion of the optimal treatment without input from the subject for improved processing efficiency.

7. The system of claim 1 , wherein the computing component modifies, using the machine learning model, the optimal treatment based on feedback from the subject.

8. A computer-implemented method, comprising:
determining, by a system operatively coupled to a processor, using one or more sensors, parameter data associated with a subject over a period of time, wherein the parameter data comprises psychological data comprising at least one psychological parameter associated with the subject, physiological data comprising at least one physiological parameter associated with the subject, behavior data comprising activities performed by the subject, treatment data comprising a group of treatments applied to the subject, and timing data comprising times associated with the parameter data; and
iteratively during the period of time:
determining, by the system, using a machine learning model, pain perception data representative of pain perception of the subject at the times based on the psychological data and the physiological data;
learning, by the system, using the machine learning model, relationships between the psychological data, the physiological data, the behavior data, the treatment data, the pain perception data, and the timing data;
generating, by the system, using the machine learning model, based on the learned relationships, an optimal treatment comprising one or more combinations of treatments from the group of treatments, and timings for administration of the one or more combinations of treatments to reduce the pain perception of the subject; and
controlling, by the system, a device associated with the subject to administer at least a portion of the optimal treatment to the subject.

9. The computer-implemented method of claim 8 , wherein the parameter data further comprises environmental data comprising at least one environmental parameter associated with the subject.

10. The computer-implemented method of claim 9 , wherein the learned relationships are further based on the environmental data.

11. The computer-implemented method of claim 8 , wherein the group of treatments comprise at least one of a medication, a wearable device, or a procedure.

12. The computer-implemented method of claim 8 , further comprising:
presenting, by the system, the optimal treatment as a suggestion to the subject via an interface that enables the subject to evaluate an effectiveness of the optimal treatment, and
receiving, by the system, input from the subject indicating whether the subject approves the optimal treatment.

13. The computer-implemented method of claim 8 , wherein the controlling the device associated with the subject to administer at least the portion of the optimal treatment to the subject occurs without input from the subject.

14. The computer-implemented method of claim 8 , further comprising modifying, by the system, using the machine learning model, the optimal treatment based on feedback from the subject.

15. A computer program product for providing pain management comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
determine, using one or more sensors, parameter data associated with a subject over a period of time, wherein the parameter data comprises psychological data comprising at least one psychological parameter associated with the subject, physiological data comprising at least one physiological parameter associated with the subject, behavior data comprising activities performed by the subject, treatment data comprising a group of treatments applied to the subject, and timing data comprising times associated with the parameter data;
iteratively during the period of time:
determine, using a machine learning model, pain perception data representative of pain perception of the subject at the times based on the psychological data and the physiological data;
learning, using the machine learning model, relationships between the psychological data, the physiological data, the behavior data, the treatment data, the pain perception data, and the timing data;
generate, using the machine learning model, based on the learned relationships, an optimal treatment comprising one or more combinations of treatments from the group of treatments, and timings for administration of the one or more combinations of treatments to reduce the pain perception of the subject; and
control a device associated with the subject to administer at least a portion of the optimal treatment to the subject.

16. The computer program product of claim 15 , wherein the parameter data further comprises environmental data comprising at least one environmental parameter associated with the subject.

17. The computer program product of claim 16 , wherein the learned relationships are further based on the environmental data.

18. The computer progra

Assignees

• IBM

Inventors

• Lin Qinghuang
• Rogers Jeffrey L
• Russo Giovanni
• SIMONETTO Andrea
• Tchrakian Tigran Tigran

Classifications

• G16H50/20 Primary

  for computer-aided diagnosis, e.g. based on medical expert systems · CPC title

• G16H50/50

  for simulation or modelling of medical disorders · CPC title

• G16H20/00

  ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance · CPC title

• G16H40/63

  for local operation · CPC title