ACTIVITY MONITORING

• US 20140074504A1
• Filed: 11/18/2013
• Published: 03/13/2014
• Est. Priority Date: 12/16/2003
• Status: Abandoned Application

• Current Assignee: Adventium Enterprises, Healthsense, Inc. (Best Buy Co., Inc.)
• Original Assignee: Adventium Enterprises, Healthsense, Inc. (Best Buy Co., Inc.)
• Inventors: Nelson, Kyle S., Bischoff, Brian J.
• Application Number:
  US14/082,671
• Publication Number:
  US 20140074504A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G08B 21/0211 Combination with medical sensor, e.g. for measuring heart rate, temperature
• CPC Class Codes: G08B 21/028 Communication between parent and child units via remote transmission means, e.g. satellite network
• CPC Class Codes: G08B 21/0283 via a telephone network, e.g. cellular GSM
• CPC Class Codes: G08B 21/0423 detecting deviation from an expected pattern of behaviour or schedule
• CPC Class Codes: G08B 21/0469 Presence detectors to detect unsafe condition, e.g. infrared sensor, microphone G08B21/0476 takes precedence
• CPC Class Codes: G08B 25/005 Alarm destination chosen according to a hierarchy of available destinations, e.g. if hospital does not answer send to police station
• CPC Class Codes: G08B 25/006 Alarm destination chosen according to type of event, e.g. in case of fire phone the fire service, in case of medical emergency phone the ambulance
• CPC Class Codes: G08B 25/016 Personal emergency signalling and security systems emergency non-personal manually actuated alarm activators G08B25/12
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

Embodiments of the present invention relate to methods, devices, and systems to monitor activity. One method to monitor activity includes monitoring a sensor activated by an individual. The method also includes recording activation of the sensor, determining a behavior routine of the individual based on recorded activations of the sensor and analyzing the recorded sensor activations to determine a behavior routine. The method also includes identifying a change in the behavior routine based on the analysis of the recorded sensor activations.

Claims

1. A method for monitoring activity, comprising:

monitoring a sensor activated by an individual;

recording activation of the sensor;

determining a behavior routine of the individual based on recorded activations of the sensor;

analyzing the recorded sensor activations to determine a behavior routine; and

identifying a change in the behavior routine based on the analysis of the recorded sensor activations.

2. The method of claim 1, further including initiating contact to a third party.

3. The method of claim 2, wherein initiating contact to a third party includes initiating contact with a third party on a hierarchical list of third party contacts.

4. The method of claim 3, wherein initiating contact with a third party on a hierarchical list includes selecting a third party based on the level of change in the behavior routine.

5. The method of claim 1, further including initiating automated contact with a third party on a hierarchical list of third party contacts.

6. The method of claim 1, further including grouping sensors within particular classes of daily activities.

7. The method of claim 6, wherein identifying a change in the at least one behavior includes comparing activations of a group of sensors within a class to a threshold.

8. The method of claim 1, wherein the method further includes providing a sensor with a level of priority.

9. The method of claim 8, wherein identifying a change in the behavior routine includes weighting sensor activations differently based upon the sensor'"'"'s level of priority.

10. The method of claim 9, wherein analyzing the recorded sensor activations to determine a behavior routine includes using a pattern recognition algorithm.

11. The method of claim 10, wherein using a pattern recognition algorithm includes using an algorithm based on a Bayesian decision theory.

12. A method for monitoring the behavior of an individual, comprising:

recording data counts from sensors activated by an individual during a time period;

identifying statistical changes in the data counts relative to expected data counts during the time period; and

initiating automated contact to a third party on a hierarchical third party list identified by the individual when a statistical change exceeds a statistical threshold value.

13. The method of claim 12, further including:

associating the data count with an activity of daily living; and

placing the data counts into groups based on activities of daily living.

14. The method of claim 13, wherein initiating automated contact to a third party on a hierarchical third party list includes analyzing the data counts in a group for a statistical change that exceeds the statistical threshold value.

15. The method of claim 12, further including setting the time period to a value of one (1) hour or greater.

16. The method of claim 12, wherein initiating automated contact to a third party on a hierarchical third party list includes identifying at least two statistical based changes that exceed the statistical threshold value.

17. The method of claim 12, wherein recording data counts from a sensor includes recording data counts from a sensor with Boolean logic.

18. A computer readable medium having a program to cause a device to perform a method, comprising:

sensing data counts associated with an activity of daily living for an individual;

determining a statistical change in the data counts relative to expected data counts for the activity of daily living;

identifying when the statistical change in the data counts relative expected data counts exceed a statistical threshold value;

selecting a third party on a hierarchical third party list based on the activity of daily living for which the statistical change in the data counts relative expected data counts exceed the statistical threshold value; and

initiating automated contact to the third party on the hierarchical third party list when the statistical based change exceeds the statistical threshold value.

19. The method of claim 18, further including adjusting the expected data counts of an activity of daily living based upon the statistical change in the data counts for the activity of daily living.

20. The method of claim 18, further including providing a predetermined amount of information about the individual and the activity of daily living to the third party on the hierarchical third party list.