System and method of remote monitoring and diagnostics for health conditions and emergency interventions

• US 9,257,029 B1
• Filed: 08/29/2013
• Issued: 02/09/2016
• Est. Priority Date: 08/29/2012
• Status: Active Grant

• Current Assignee: Andrew Thomas Johnson, James E. Anderson III, James Robert Iii Hendrick, Jonathan Eddy Barnes
• Original Assignee: James E. Anderson III, James Robert Iii Hendrick
• Inventors: Hendrick, James Robert III, Barnes, Jonathan Eddy, Johnson, Andrew Thomas, Anderson, James E. III
• Primary Examiner(s): Blount, Eric
• Application Number:
  US14/013,114
• Time in Patent Office: 894 Days
• Field of Search: 340/573.1, 340/539.11, 340/539.12, 340/3.1, 600/300, 600/301
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 50/22 Social work or social welfare, e.g. community support activities or counselling services
• CPC Class Codes: G08B 21/0415 detecting absence of activity per se
• CPC Class Codes: G08B 21/0423 detecting deviation from an expected pattern of behaviour or schedule
• CPC Class Codes: G08B 21/043 detecting an emergency event, e.g. a fall
• CPC Class Codes: G08B 21/0492 Sensor dual technology, i.e. two or more technologies collaborate to extract unsafe condition, e.g. video tracking and RFID tracking
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

An automated healthcare intervention system includes biometric and activity sensors in a residential area. A server stores base data for an associated healthcare subject in a data storage network, and leverages the base data to infer temporal relationships with respect to potential conditions for the subject. The server determines that an event requiring intervention has occurred by comparing combinations of base data and inferred temporal relationships with associated time ranges and threshold values, and delivers an intervention prompt to an associated healthcare provider. Post-event monitoring allows for predictive analysis with respect to future occurrences of a similar event, and further enables determination of a severity of the event, for example a fall. Defined sleeping areas or food storage areas may be monitored over time and with respect to defined patterns and healthcare conditions of the subject to identify sleeping or eating disorders.

Claims

1. A system for diagnosing and prompting healthcare interventions, the system comprising:

a first set of one or more sensors disposed in a defined area and effective to generate output signals representative of biometric data for a healthcare subject;

a second set of one or more sensors disposed in the defined area and effective to generate output signals representative of activity within the defined area;

a server functionally linked via a communications network to the sensors and further comprising a data processor, a data storage network and a non-transitory computer-readable medium having program instructions residing thereon, the instructions executable by the processor to direct the performance of operations further comprising;

storing base data comprising time-specific biometric and activity data points for the subject in the data storage network,

determining derivative data comprising one or more inferred temporal relationships with respect to the base data;

determining an event requiring intervention by comparing one or more combinations of base data and derivative data with associated intervention criteria comprising one or more of temporal ranges and threshold values;

post-event monitoring of activity data to determine a severity of a respective event;

aggregating data comprising one or more determined events, a determined severity of the events, and associated base data and derivative data in the data storage network;

reverse analyzing post-event activity and pre-event activity represented by the aggregated data as predictive indicators of a future likelihood of such events and a likely severity of such events;

dynamically adjusting one or more intervention criteria based on the predictive indicators; and

delivering an intervention prompt to a healthcare provider associated with the subject, the intervention prompt prioritized based on a relative post-event activity level of the subject with respect to a pre-event activity level.

2. The system of claim 1, further comprising instructions executable to direct the performance of an operation of enabling users to provide input relevant to a healthcare profile for the subject, wherein an initial set of intervention criteria is defined based in part on the healthcare profile.

3. The system of claim 1, wherein intervention criteria associated with the subject are dynamically adjusted over time based on determined events and patterns in the stored base data and determined derivative data.

4. The system of claim 1, wherein one or more inferred temporal relationships as derivative data comprise an inferred period of inactivity with respect to at least a portion of the defined area.

5. The system of claim 1, wherein one or more inferred temporal relationships as derivative data comprise an inferred frequency of activity with respect to at least a portion of the defined area.

14. The system of claim 1, further comprising instructions executable to direct an operation of:

posting social media status updates comprising one or more of flagged base data and flagged derivative data for presentation in an integrated social media account.

15. The system of claim 14, wherein said social media status updates are posted on behalf of the subject, with the subject being denied access to post to the account.

6. A system for diagnosing and prompting healthcare interventions, the system comprising:

a set of one or more sensors disposed in a defined living area for a healthcare subject, the sensors effective to generate output signals representative of activity within the area;

a server functionally linked via a communications network to the one or more sensors and further comprising a data processor, a data storage network and a non-transitory computer-readable medium having program instructions residing thereon, the instructions executable by the processor to direct the performance of operations further comprising;

storing time-specific activity data points for the subject in the data storage network,

determining derivative data comprising one or more inferred temporal relationships with respect to the activity data points;

identifying one or more periods of inactivity in at least a portion of the defined area from the derivative data, the one or more periods of inactivity having at least a threshold duration;

determining a fall by the subject wherein one or more of the identified periods of inactivity correspond to a period of expected activity;

post-event monitoring of activity data point and derivative data to determine a severity of the fall;

aggregating data comprising one or more determined falls, a determined severity of the respective falls, and associated base data and derivative data in the data storage network;

reverse analyzing post-fall activity and pre-fall activity represented by the aggregated data as predictive indicators of a future likelihood of falls and a likely severity of such falls;

dynamically adjusting one or more of the threshold duration for inactivity and the period of expected activity based on the predictive indicators; and

delivering an intervention prompt to a healthcare provider associated with the subject, the intervention prompt prioritized based on a relative post-fall activity level of the subject with respect to a pre-fall activity level.

7. The system of claim 6, wherein the operation of identifying one or more periods of inactivity comprises identifying a lack of movement in the defined area for a first period of time and a lack of use in a defined sleeping area for the first period of time, the first period of time having a duration exceeding a threshold duration associated with determining a fall by the subject.

8. The system of claim 6, wherein the operation of identifying one or more periods of inactivity comprises identifying a lack of movement with respect to one or more of:

a defined food storage area for a first period of time, the first period of time having a duration exceeding a threshold duration associated with determining an eating disorder for the subject, and

a defined sleeping area for a second period of time, the second period of time having a duration exceeding a threshold duration associated with determining a sleeping disorder for the subject.

16. The system of claim 6, further comprising instructions executable to direct an operation of:

posting social media status updates comprising one or more of flagged base data and flagged derivative data for presentation in an integrated social media account.

17. The system of claim 16, wherein said social media status updates are posted on behalf of the subject, with the subject being denied access to post to the account.

9. A system for diagnosing and prompting healthcare interventions, the system comprising:

a set of one or more sensors disposed in a defined living area for a healthcare subject, the sensors effective to generate output signals representative of activity within the area;

a server functionally linked via a communications network to the one or more sensors and further comprising a data processor, a data storage network and a non-transitory computer-readable medium having program instructions residing thereon, the instructions executable by the processor to direct the performance of operations further comprising;

storing time-specific activity data points for the subject in the data storage network,

determining derivative data comprising one or more inferred temporal relationships with respect to the activity data points;

identifying a duration or frequency of activity with respect to at least a portion of the defined area from the derivative data;

determining an event requiring intervention wherein the respective duration or frequency of activity exceeds a threshold value for the subject;

post-event monitoring of activity data to determine a severity of the event;

aggregating data comprising one or more determined events, a determined severity of the respective events, and associated base data and derivative data in the data storage network;

reverse analyzing post-event activity and pre-event activity represented by the aggregated data as predictive indicators of a future likelihood of such events and a likely severity of such events;

dynamically adjusting one or more of the threshold value for the respective duration and the threshold value for the frequency of activity, based on the predictive indicators; and

delivering an intervention prompt to a healthcare provider associated with the subject, the intervention prompt prioritized based on a relative post-event activity level of the subject with respect to a pre-event activity level.

10. The system of claim 9, wherein the operation of identifying a duration or frequency of activity comprises identifying one or more breaches with respect to one or more perimeter portions of the defined area during an expected sleeping time associated with the subject.

11. The system of claim 10, further comprising instructions executable to direct the performance of operations of

aggregating data comprising determined breaches, associated activity data and associated derivative data in the data storage network, and

implementing the aggregated data as predictive indicators of future breaches.

12. The system of claim 9, wherein the operation of identifying a duration or frequency of activity comprises identifying a frequency of access to a defined food storage area over a first period of time, the identified frequency exceeding a threshold value associated with determining an eating disorder for the subject.

13. The system of claim 9, wherein the operation of identifying a duration or frequency of activity comprises identifying use of a defined sleeping area for a first period of time, the first period of time having a duration exceeding a threshold duration associated with determining a sleeping disorder for the subject.

18. The system of claim 9, further comprising instructions executable to direct an operation of:

posting social media status updates comprising one or more of flagged base data and flagged derivative data for presentation in an integrated social media account.

19. The system of claim 18, wherein said social media status updates are posted on behalf of the subject, with the subject being denied access to post to the account.