Activity monitoring

• US 8,589,174 B2
• Filed: 12/16/2003
• Issued: 11/19/2013
• Est. Priority Date: 12/16/2003
• Status: Active Grant

• Current Assignee: Best Buy Health Incorporated (Best Buy Co., Inc.)
• Original Assignee: Adventium Enterprises
• Inventors: Nelson, Kyle S., Bischoff, Brian J.
• Primary Examiner(s): Najarian, Lena
• Assistant Examiner(s): WOODS, TERESA S
• Application Number:
  US10/737,076
• Publication Number:
  US 20050131736A1
• Time in Patent Office: 3,626 Days
• Field of Search: 705 2- 4, 600/300, 607/60, 340540-548
• 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, by a computing device having a computer processor and computer-readable code stored on a computer-readable medium and executable by the computer processor, a number of sensors activated by an individual, wherein the number of sensors are located in a dwelling of the individual;

recording activations of the number of sensors on the computing device in communication with the number of sensors;

determining a behavior routine of the individual with the computing device based on recorded activations of the number of sensors, wherein a number of patterns of a number of sensor activations are identified that indicate the individual performing a number of activities that make up the behavior routine;

identifying a statistical change in the behavior routine with the computing device based on an analysis of the recorded sensor activations, wherein the analysis includes a comparison of the recorded sensor activations to a threshold;

determining, with the computing device, a confidence level of the identification of the change in the behavior routine, wherein the confidence level is based on the analysis of the statistical changes in the data counts relative to expected data counts of sensor activations of a first group of the number of sensors with sensor activations of one or more groups of the number of sensors and wherein the confidence level provides a level of certainty that the change in the statistical changes in the data counts relative to expected data counts have exceeded a statistical threshold value; and

initiating contact to a third party on a hierarchical list of third party contacts with the computing device in response to identifying the change in the behavior routine, wherein the third party on the hierarchical list to contact is selected based on a level of change in the behaviour routine and the confidence level.

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

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

4. The method of claim 3, wherein identifying a change in the behavior routine includes comparing activations of a group of sensors within a class to a threshold.

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

6. The method of claim 5, wherein identifying a change in the behavior routine includes weighting sensor activations differently based upon the sensor'"'"'s level of priority.

7. The method of claim 6, wherein determining the behavior routine includes using a pattern recognition algorithm.

8. The method of claim 7, wherein using a pattern recognition algorithm includes using an algorithm based on a Bayesian decision theory.

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

recording, by a computing device having a computer processor and computer-readable code stored on a computer-readable medium and executable by the computer processor, data counts from a number of sensors activated by an individual during a time period on the computing device in communication with the number of sensors to determine a behavior routine of the individual, wherein the number of sensors are located in a dwelling of the individual and a number of patterns of the data counts are identified that indicate the individual performing a number of activities that make up the behavior routine;

identifying statistical changes in the data counts relative to expected data counts during the time period with the computing device;

determining, with the computing device, a confidence level of the statistical changes in the data counts relative to expected data counts based on the statistical changes in the data counts relative to expected data counts and a comparison of data counts from a first group of the number of sensors with data counts from one or more groups of the number of sensors, wherein the confidence level provides a level of certainty that the statistical changes in the data counts relative to expected data counts have exceeded a statistical threshold value; and

initiating automated contact to a third party on a hierarchical third party list with the computing device identified by the individual when a statistical change exceeds the statistical threshold value, wherein the third party on the hierarchical list to contact is selected based on a level of statistical change and the confidence level.

10. The method of claim 9, further including:

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

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

11. The method of claim 10, 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.

12. The method of claim 10, wherein identifying statistical changes in the data counts includes:

developing an expected count for the activity of daily living over the time period; and

initiating automated contact to a third party on the hierarchical third party list when the recorded counts are statistically less than the expected count for the activity of daily living over the time period.

13. The method of claim 9, further including setting the time period to a value of one (1) hour or greater.

14. The method of claim 9, 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.

15. The method of claim 9, wherein recording data counts from a sensor includes recording data counts from a sensor with Boolean logic.

16. The method of claim 9, further including self-diagnosing an operational condition of a monitoring system based on the recorded data counts.

17. The method of claim 16, further including diagnosing an operational condition of a sensor in the monitoring system.

18. The method of claim 9, wherein initiating automated contact to a third party on a hierarchical third party list includes prompting the individual to confirm that automated contact to the third party should be made.

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

sensing data counts associated with a number of activities of daily living for an individual, wherein the data counts are from activations of a number of sensors that are located in a dwelling of an individual;

determining a behavior routine of the individual based on the sensed data counts, wherein a number of patterns of the sensed data counts are identified that indicate the individual performing the number of activities of daily living that make up the behavior routine;

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;

determining a confidence level of the statistical change in the data counts relative expected data counts based on the statistical change in the data counts relative to expected data counts and a comparison of data counts from a first group of the number of sensors with data counts from one or more groups of the number of sensors, wherein the confidence level of the statistical change provides a level of certainty that the statistical change has exceeded the 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, a level of statistical change in the data counts, and the confidence level; and

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

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

21. The method of claim 19, further including providing a predetermined amount of information about the individual and the number of activities of daily living to the third party on the hierarchical third party list.

22. The method of claim 19, wherein the initiating automated contact to a third party on a hierarchical third party list further includes prompting the individual to confirm that automated contact to the third party should be made.

23. The method of claim 19, further including placing the third party contacts in tiers of third party contacts wherein at least one tier includes multiple third party contacts.

24. The method of claim 19, further including:

requesting automated contact to the third party on the hierarchical third party list by the individual; and

initiating the automated contact to the third party on the hierarchical third party list at the request of the individual.

25. The method of claim 19, further including identifying a sensor that is not transmitting data counts based on the statistical change in the data counts of the sensor relative to expected data counts for the sensor.

26. The method of claim 25, further including adjusting the expected data counts for the sensor based upon the statistical change in the data counts.

27. A system to monitoring activity, comprising:

means for signaling that a number of sensors have been activated by an individual during activities of daily living, wherein the number of sensors include sensors located in a dwelling of the individual;

a receiver to receive signals, indicating that the number of sensors have been activated;

a tabulation unit including a computing device to tabulate the number of received signals;

an analysis unit including a computing device to analyze the statistical tabulated signals to determine a behavior routine, identify changes in the behavior routine, and determine a confidence level of the identified changes in the behavior routine based on the changes in the behavior routine and a comparison of the number of received signals from a first group of the number of sensors with the number of received signals from one or more groups of the number of sensors, wherein the confidence level provides a level of certainty that the statistical changes in the behavior routine occurred and wherein a number of patterns of a number of sensor activations are identified that indicate the individual performing the activities of daily living that make up the behavior routine; and

a contacting unit including a computing device to initiate contact with a third party selected from a hierarchical list of third party contacts when the analysis unit identifies a defined level change in the behavior routine.

28. The system of claim 27, wherein means for signaling includes a sensor worn by the individual.

29. The system of claim 28, wherein the sensor worn by the individual is a sensor that is actuated when the sensor is located within a range that includes the dwelling and a portion of land on which the dwelling is situated.

30. The system of claim 27, wherein means for signaling includes digital sensors.

31. The system of claim 27, wherein the means for signaling includes analog sensors.

32. The system of claim 31, wherein the analog sensors produce a Boolean output.

33. A device for monitoring activity, comprising:

a receiver to receive activation signals from a number of sensors activated by an individual during activities of daily living, wherein the number of sensors include sensors located in a dwelling of the individual;

a processing unit including a computing device to tabulate the received signals to determine a behavior routine, identify changes in the behavior routine, and determine a confidence level of the identified changes in the behavior routine based on the statistical changes and a comparison of the number of received signals from a first group of the number of sensors with the number of received signals from one or more groups of the number of sensors, wherein the confidence level provides a level of certainty that the statistical changes in the behavior routine occurred and wherein a number of patterns of the received activation signals are identified that indicate the individual performing the activities of daily living that make up a behavior routine; and

a contacting unit to initiate contact with a third party selected from a hierarchical list of third party contacts based on a defined level of change in a behavior routine and the confidence level when directed by the processing unit.

34. The device of claim 33, wherein the device is a self contained, stand-alone device.

35. The device of claim 34, wherein the device includes an additional functionality selected from:

a radio, a clock radio, an alarm clock, a telephone, and an answering machine.