State characterization based on multi-variate data fusion techniques

• US 10,682,071 B2
• Filed: 03/24/2017
• Issued: 06/16/2020
• Est. Priority Date: 07/08/2008
• Status: Active Grant

• Current Assignee: Proteus Digital Health, Inc. (Otsuka Holdings Company Limited)
• Original Assignee: Proteus Digital Health, Inc. (Otsuka Holdings Company Limited)
• Inventors: Behzadi, Yashar
• Primary Examiner(s): Jang, Christian
• Application Number:
  US15/469,052
• Publication Number:
  US 20170303818A1
• Time in Patent Office: 1,180 Days
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/07 Endoradiosondes
• CPC Class Codes: A61B 5/117 Identification of persons methods or arrangements for recognising patterns, e.g. fingerprints, G06F18/00, G06V40/00; identification of persons by analysing their voice or speech G10L17/00
• CPC Class Codes: A61B 5/4833 Assessment of subject's compliance to treatment
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: G16H 10/65 stored on portable record carriers, e.g. on smartcards, RFID tags or CD
• CPC Class Codes: G16H 20/00 ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 70/40 relating to drugs, e.g. their side effects or intended usage
• CPC Class Codes: G16H 80/00 ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
• CPC Class Codes: G16Y 20/40 relating to personal data, e.g. biometric data, records or preferences
• CPC Class Codes: G16Y 40/10 Detection; Monitoring

Abstract

The disclosed system includes an ingestible event marker device configured to collect Ingestible Event Marker (IEM) data from a body of an individual and transmit a signal including the IEM data, wherein the IEM data include information associated with an ingestion event, a receiver adapted to be associated with the body of the individual and configured to receive the signal including the IEM data via the body of the individual, a hub to receive the IEM data from the receiver, and at least one IEM data system to receive the IEM data from the hub. The at least one IEM data system analyzes the IEM data and generates at least one metric based on the IEM data. The at least one IEM data system may further generate predictive information based on the at least one metric, wherein the predictive information is related to prediction of a state of the individual.

Claims

1. A system comprising:

an ingestible event marker device configured to collect Ingestible Event Marker (IEM) data from a body of an individual and transmit a signal comprising the IEM data, wherein the IEM data comprise information associated with an ingestion event;

a receiver adapted to be associated with the body of the individual, the receiver configured to receive the signal comprising the IEM data via the body of the individual associated with the receiver;

a hub configured to receive the IEM data from the receiver; and

at least one IEM data system configured to;

receive the IEM data from the hub;

analyze the IEM data and generate at least one metric based on the IEM data; and

generate predictive information based on the at least one metric, wherein the predictive information is related to a prediction of a state of the individual.

2. The system of claim 1, wherein the receiver is selected from a group consisting of a patch receiver, an implantable receiver, a receiver configured to be worn on the body, an apparel-configured receiver, and a receiver adapted to be associated with the hub.

3. The system of claim 2, wherein the receiver adapted to be associated with the hub comprises a mobile phone attachment.

4. The system of claim 3, wherein the hub is a mobile phone.

5. The system of claim 1, wherein the at least one IEM data system further comprises software.

6. The system of claim 5, wherein the software further comprises at least one of an analysis module, a metrics module, and a predictive information module.

7. The system of claim 6, wherein the analysis module analyzes the IEM data.

8. The system of claim 6, wherein the metrics module generates the at least one metric based on the IEM data.

9. The system of claim 6, wherein the predictive information module generates the predictive information based on the IEM data.

10. The system of claim 6, wherein:

the IEM data further comprise physiologic data,

the analysis module analyzes the physiologic data and generates the at least one metric based on the physiologic data, and

the predictive module generates the predictive information based on the physiologic data.

11. The system of claim 1, wherein the at least one IEM data system comprises at least one of a feedback loop system and a decision support system.

12. The system of claim 1, wherein the receiver is configured to capture the IEM data at a predetermined rate.

13. The system of claim 1, wherein the IEM data comprises information relating to a dosage of medication.

14. The system of claim 1, wherein the receiver is configured to transmit additional data to the hub, and the at least one IEM data system to receive the additional data from the hub, wherein the additional data comprises data derived from the receiver.

15. The system of claim 14, wherein the at least one IEM data system analyzes the additional data derived from the receiver and generates at least one metric based on the IEM data and the additional data derived from the receiver.

16. The system of claim 14, wherein the additional data derived from the receiver comprises information regarding at least one of positional data, accelerometer data, dosing time, galvanic skin response, heat-flux, heart rate, or heart rate variability.

17. The system of claim 1, wherein the at least one metric comprises a circadian pattern of the individual.

18. The system of claim 17, wherein the at least one metric comprises a standard deviation of the circadian pattern of the individual across a predetermined number of days and an overall variability of the circadian pattern of the individual.

19. The system of claim 1, wherein the at least one metric comprises blood pressure, blood pressure increase over time, and blood pressure increase compared to dosing and dose type.

20. The system of claim 1, wherein the at least one IEM data system analyzes the IEM data such that the IEM data are time-normalized and interpolated to a time of day.

21. A system comprising:

an Ingestible Event Marker (IEM) device configured to collect IEM data from a body of an individual associated with the IEM device and transmit a signal comprising the IEM data, wherein the IEM data comprise information associated with an ingestion event; and

at least one IEM data system configured to process the IEM data, the at least one IEM data system comprising a processor and a non-transitory machine readable medium, wherein the non-transitory machine readable medium comprises instructions that when executed by the processor cause the processor to;

analyze the IEM data and generate at least one metric based on the IEM data; and

generate predictive information based on the at least one metric, wherein the predictive information is related to a prediction of a state of the individual;

wherein the IEM data is received from the body of the individual.

22. The system of claim 21, wherein the predictive information is associated with a likelihood of adherence to a medication regimen.

23. The system of claim 21, wherein the predictive information is associated with the prediction of occurrence of a future health event.

24. The system of claim 21, wherein the predictive information is associated with a characterization of patient stability while on a medication regimen.

25. A system comprising:

an ingestible event marker device configured to collect Ingestible Event Marker (IEM) data from a body of an individual and transmit a signal comprising the IEM data, wherein the IEM data comprise information associated with an ingestion event;

a receiver adapted to be associated with the body of the individual, the receiver configured to receive the signal comprising the IEM data via the body of the individual associated with the receiver;

a hub configured to receive the IEM data; and

at least one IEM data system configured to;

receive the IEM data from the hub;

analyze the IEM data and generate at least one metric based on the IEM data; and

generate predictive information based on the at least one metric;

wherein the predictive information comprises an indication of a likelihood of adherence to a medication regimen.