Activity monitoring

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.

What is claimed is: 
     
         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.