Computational systems and methods for monitoring medication events

• US 9,390,234 B2
• Filed: 06/16/2014
• Issued: 07/12/2016
• Est. Priority Date: 08/24/2012
• Status: Active Grant

• Current Assignee: Elwha LLC (Intellectual Ventures LLC)
• Original Assignee: Elwha LLC (Intellectual Ventures LLC)
• Inventors: Bangera, Mahalaxmi Gita, Hyde, Roderick A., Kare, Jordin T., Leuthardt, Eric C., Sweeney, Elizabeth A., Wood, Lowell L. Jr.
• Primary Examiner(s): Hofsass, Jeffery
• Application Number:
  US14/305,210
• Publication Number:
  US 20140297312A1
• Time in Patent Office: 757 Days
• Field of Search: 340/573.1, 340/539.12, 340/309.16, 600/300, 368/10, 705/2
• US Class Current: 1/1
• CPC Class Codes: A61J 2200/30 Compliance analysis for taking medication
• CPC Class Codes: A61J 7/04 Arrangements for time indication or reminder for taking medicine, e.g. programmed dispensers
• CPC Class Codes: G16H 20/13 delivered from dispensers
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

Computer-based systems and computer-implemented methods are described for monitoring medication events for an individual. Computer-based systems include systems for monitoring medication events relating to an individual, including: circuitry for analyzing data for an identifier of a first medication event for an individual; circuitry for analyzing the data for at least one attribute of an individual; circuitry for analyzing the data for at least one attribute relating to a medication during the first medication event; circuitry for analyzing the data for at least one feature of visual information and at least one feature of non-visual information relating to the individual during the first medication event; circuitry for analyzing the received data for a time associated with the first medication event; circuitry for determining a compliance likelihood for the first medication event based on the analyzes of the received data; and circuitry for indicating the determined compliance likelihood.

Claims

1. A method for monitoring medication events relating to an individual, comprising:

analyzing received data for an identifier of a first medication event for an individual, the received data originating from at least one monitoring device;

analyzing the received data for at least one attribute of an individual;

analyzing the received data for at least one attribute relating to a medication during the first medication event;

analyzing the received data for at least one feature of visual information relating to the individual during the first medication event;

analyzing the received data for at least one feature of non-visual information relating to the individual during the first medication event;

analyzing the received data for a time associated with the first medication event;

determining a compliance likelihood for the first medication event based on the analyses of the received data; and

indicating the determined compliance likelihood for the first medication event.

2. The method of claim 1, wherein the analyzing received data for an identifier of a first medication event for an individual comprises:

analyzing received data for an identifier that includes at least one non-visual information feature.

3. The method of claim 1, wherein the analyzing the received data for at least one attribute of the individual comprises:

analyzing the received data for at least one attribute of the individual;

comparing the at least one attribute of the individual with a set of attribute parameters for an expected individual;

determining, based on the comparison, an attribute score for the at least one attribute of the individual.

4. The method of claim 1, wherein the analyzing the received data for at least one feature of visual information relating to the individual during the first medication event comprises:

identifying a visual information component of the received data;

comparing the identified visual information component of the received data with at least one visual information parameter; and

determining a likelihood of sufficiency for the visual information component of the received data based on the comparison.

5. The method of claim 1, wherein the analyzing the received data for at least one feature of non-visual information relating to the individual during the first medication event comprises:

analyzing the received data for at least one feature of non-visual information including auditory information.

6. The method of claim 1, wherein the analyzing the received data for at least one feature of non-visual information relating to the individual during the first medication event comprises:

identifying a non-visual information component of the received data;

comparing the identified non-visual information component of the received data with at least one non-visual information parameter; and

determining a likelihood of sufficiency for the non-visual information component of the received data based on the comparison.

7. The method of claim 1, comprising:

comparing the determined compliance likelihood for the first medication event to a determined compliance likelihood for a second medication event for the individual;

comparing the determined compliance likelihood for the first medication event and the determined compliance likelihood for the second medication event to a compliance goal for the individual; and

indicating the comparison.

8. The method of claim 1, comprising:

comparing the analyses with a set of standard analysis parameters for a standard medication event;

determining, based on the comparison, if the analyses are within the standard analysis parameters for a standard medication event; and

indicating the determination.

9. The method of claim 1, comprising:

analyzing received data for an identifier of a second medication event for the individual;

analyzing received data for the at least one attribute of the individual;

analyzing the received data for the at least one attribute relating to a medication during the second medication event;

analyzing the received data for at least one feature of visual information relating to the individual during the second medication event;

analyzing the received data for at least one feature of non-visual information relating to the individual during the second medication event;

analyzing the received data for a time associated with the second medication event;

determining a compliance likelihood for the second medication event based on the analyses of the received data; and

indicating the determined compliance likelihood for the second medication event.

10. A method for monitoring medication events, comprising:

accepting data regarding a medication event for an individual;

extracting, from the accepted data regarding the medication event for the individual, one or more identifiers of the medication;

comparing the one or more identifiers of the medication with a set of standard medication identifier parameters;

extracting, from the accepted data regarding the medication event for the individual, one or more visual features of the medication event;

comparing the one or more visual features of the medication event with a set of medication event parameters;

extracting, from the accepted data regarding the medication event for the individual, one or more non-visual features of the medication event;

comparing the one or more non-visual features of the medication event with the set of medication event parameters;

extracting, from the accepted data regarding the medication event for the individual, a time associated with the medication event;

comparing the time associated with the medication event with an expected medication event time for the individual; and

saving the comparisons into a memory.

11. The method of claim 10, wherein the accepting data regarding a medication event for an individual comprises:

accepting data originating from a plurality of devices.

12. The method of claim 10, wherein the extracting, from the accepted data regarding a medication event for the individual, one or more visual features of the medication event comprises:

extracting one or more visual features over time.

13. The method of claim 10, wherein the comparing the one or more visual features of the medication event with a set of medication event parameters comprises:

determining, from a set of standard medication event visual features, at least one expected visual feature; and

comparing the accepted data regarding a medication event for the individual with the determined at least one expected visual feature.

14. The method of claim 10, wherein the extracting, from the accepted data regarding a medication event for the individual, one or more non-visual features of the medication event comprises:

extracting one or more non-visual features over time.

15. The method of claim 10, wherein the extracting, from the accepted data regarding a medication event for the individual, one or more non-visual features of the medication event comprises:

extracting one or more audio features.

16. The method of claim 10, wherein the extracting, from the accepted data regarding a medication event for the individual, one or more non-visual features of the medication event comprises:

extracting one or more near-infrared (IR) features.

17. The method of claim 10, wherein the extracting, from the accepted data regarding a medication event for the individual, one or more non-visual features of the medication event comprises:

extracting one or more thermal features.

18. The method of claim 10, wherein the comparing the one or more non-visual features of the medication event with a set of medication event parameters comprises:

determining, from a set of standard medication event non-visual parameters, expected parameters for at least one expected non-visual feature; and

comparing the accepted data regarding a medication event for the individual with the expected parameters for at least one expected non-visual feature.

19. The method of claim 10, wherein the extracting, from the accepted data regarding a medication event for the individual, a time associated with the medication event comprises:

extracting a time interval associated with the medication event.

20. The method of claim 10, wherein the comparing the time associated with the medication event with an expected medication event time for the individual comprises:

determining, from a set of standard medication event times, at least one expected medication event time; and

comparing the extracted time associated with the medication event with the determined at least one expected medication event time.

21. The method of claim 10, comprising:

accepting data regarding a second medication event for the individual;

extracting, from the accepted data regarding the second medication event for the individual, one or more identifiers of the medication;

comparing the one or more identifiers of the medication with a set of standard medication identifier parameters;

extracting, from the accepted data regarding the second medication event for the individual, one or more visual features of the medication event;

comparing the one or more visual features of the second medication event with a set of medication event parameters;

extracting, from the accepted data regarding the second medication event for the individual, one or more non-visual features of the second medication event;

comparing the one or more non-visual features of the second medication event with the set of medication event parameters;

extracting, from the accepted data regarding the second medication event for the individual, a time associated with the second medication event;

comparing the time associated with the second medication event with an expected second medication event time for the individual; and

saving the comparisons associated with the second medication event into a memory.

22. A system for monitoring medication events relating to an individual, comprising:

circuitry for analyzing received data encoded on a transmission originating from a cell phone for an identifier of a first medication event for an individual, wherein the received data;

circuitry for analyzing the received data for at least one attribute of an individual;

circuitry for analyzing the received data for at least one attribute relating to a medication during the first medication event;

circuitry for analyzing the received data for at least one feature of visual information relating to the individual during the first medication event;

circuitry for analyzing the received data for at least one feature of non-visual information relating to the individual during the first medication event;

circuitry for analyzing the received data for a time associated with the first medication event;

circuitry for determining a compliance likelihood for the first medication event based on the analyses of the received data; and

circuitry for indicating the determined compliance likelihood for the first medication event.

23. The system of claim 22, wherein the circuitry for analyzing the received data for at least one attribute of the individual comprises:

circuitry for associating the identifier of the first medication event with an expected individual;

circuitry for retrieving one or more specific identifiers associated with the expected individual;

circuitry for analyzing the received data for the presence or absence of at least one of the one or more specific identifiers; and

circuitry for indicating the presence or absence of the expected individual based on the analysis.

24. A computer-readable non-transitory storage medium including executable instructions for monitoring medication events relating to an individual, the computer-readable storage medium comprising:

instructions for analyzing received data encoded on a transmission originating from a cell phone for an identifier of a first medication event for an individual;

instructions for analyzing the received data for at least one attribute of an individual;

instructions for analyzing the received data for at least one attribute relating to a medication during the first medication event;

instructions for analyzing the received data for at least one feature of visual information relating to the individual during the first medication event;

instructions for analyzing the received data for at least one feature of non-visual information relating to the individual during the first medication event;

instructions for analyzing the received data for a time associated with the first medication event;

instructions for determining a compliance likelihood for the first medication event based on the analyses of the received data; and

instructions for indicating the determined compliance likelihood for the first medication event.

25. The computer-readable non-transitory storage medium of claim 24, wherein the instructions for analyzing the received data for at least one attribute of the individual comprises:

instructions for associating the identifier of the first medication event with an expected individual;

instructions for retrieving one or more specific identifiers associated with the expected individual;

instructions for analyzing the received data for the presence or absence of at least one of the one or more specific identifiers; and

instructions for indicating the presence or absence of the expected individual based on the analysis.

26. A system for monitoring medication events, comprising:

circuitry for accepting data regarding a medication event for an individual;

circuitry for extracting, from the accepted data regarding the medication event for the individual, one or more identifiers of the medication;

circuitry for comparing the one or more identifiers of the medication with a set of standard medication identifier parameters;

circuitry for extracting, from the accepted data regarding the medication event for the individual, one or more visual features of the medication event;

circuitry for determining, from a set of standard medication event visual features, at least one expected visual feature;

circuitry for comparing the accepted data regarding the medication event for the individual with the determined at least one expected visual feature;

circuitry for extracting, from the accepted data regarding the medication event for the individual, one or more non-visual features of the medication event;

circuitry for comparing the one or more non-visual features of the medication event with the set of medication event parameters;

circuitry for extracting, from the accepted data regarding the medication event for the individual, a time associated with the medication event;

circuitry for comparing the time associated with the medication event with an expected medication event time for the individual; and

circuitry for saving the comparisons into a memory.

27. The system of claim 26, wherein the circuitry for extracting, from the accepted data regarding the medication event for the individual, the one or more non-visual features of the medication event comprises:

circuitry for extracting the one or more non-visual features over time.

28. A computer-readable non-transitory storage medium including executable instructions for monitoring medication events relating to an individual, the computer-readable storage medium comprising:

instructions for accepting data regarding a medication event for an individual;

instructions for extracting, from the accepted data regarding the medication event for the individual, one or more identifiers of the medication;

instructions for comparing the one or more identifiers of the medication with a set of standard medication identifier parameters;

instructions for extracting, from the accepted data regarding the medication event for the individual, one or more visual features of the medication event;

instructions for determining, from a set of standard medication event visual features, at least one expected visual feature;

instructions for comparing the accepted data regarding the medication event for the individual with the determined at least one expected visual feature;

instructions for extracting, from the accepted data regarding the medication event for the individual, one or more non-visual features of the medication event;

instructions for comparing the one or more non-visual features of the medication event with the set of medication event parameters;

instructions for extracting, from the accepted data regarding the medication event for the individual, a time associated with the medication event;

instructions for comparing the time associated with the medication event with an expected medication event time for the individual; and

instructions for saving the comparisons into a memory.