Activity analysis, fall detection and risk assessment systems and methods

Abstract

A method for determining the risk of a person falling is provided. The method includes acquiring depth image data that comprises a plurality of frames that depict a person walking through a home, and extracting a foreground object from the depth image data. The method additionally includes generating a three-dimensional data object based on the foreground object, and identifying a walking sequence from the three-dimensional data object. The method further includes generating one or more gait parameters from the identified walking sequence, and comparing the one or more gait parameters against a standard clinical measure of the one or more gait parameters to determine a level of risk at which the person is of falling.

What is claimed is: 
     
         1 . A method for determining the risk of a person to falling, the method comprising:
 acquiring by at least one processor of a computer-based remote device, depth image data from at least one depth camera, wherein the depth image data comprises a plurality of frames that depict the person walking through a home environment over time, the frames comprising a plurality of pixels, the remote device located remotely from the at least one depth camera, the remote device comprising electronic memory on which an image analysis application is electronically stored, and the at least one processor structured and operable to execute the image analysis application;   extracting, by the at least one processor, a foreground object from the depth image data;   segmenting, by the at least one processor, the pixels of the frames of the depth image data corresponding to the foreground object;   generating, by the at least one processor, a three-dimensional data object based on the foreground object;   tracking by the at least one processor, the three-dimensional data object over a plurality of frames of the depth images data;   identifying, by the at least one processor, a walking sequence from the tracked three-dimensional data object, wherein the identifying comprises:
 the at least one processor determining a speed for the tracked three-dimensional data object over a time frame; 
 the at least one processor comparing the determined speed with a speed threshold; 
 in response to the comparison indicating that the determined speed is greater than the speed threshold, the at least one processor assigning a state indicative of walking to the tracked three-dimensional data object; 
 while the tracked three-dimensional data object is in the assigned walking state:
 the at least one processor determining a walk straightness for the tracked three-dimensional data object; 
 the at least one processor determining a walk length for the tracked three-dimensional data object; 
 the at least one processor determining a walk duration for the tracked three-dimensional data object; 
 the at least one processor saving the tracked three-dimensional data object in memory as the identified walking sequence if the determined walk straightness exceeds a straightness threshold, the determined walk length exceeds a walk length threshold, and the determined walk duration exceeds a walk duration threshold; 
 
   generating, by the at least one processor, one or more gait parameters from the identified walking sequence;   comparing, by the at least one processor, the one or more gait parameters against a standard clinical measure of the one or more gait parameters to determine a level of risk at which the person is of falling.   
     
     
         2 . The method of  claim 1 , wherein the identified walking sequence is compared against a previously saved walking sequence of the person to confirm that the identified walking sequence is correctly associated with the person. 
     
     
         3 . The method of  claim 2 , wherein the comparison utilizes a Gaussian distribution. 
     
     
         4 . The method of  claim 1 , wherein the one or more gait parameters includes at least one of: walking speed, stride time, or stride length. 
     
     
         5 . The method of  claim 1 , wherein the standard clinical measure is selected from the group consisting of: Timed-Up-and-Go (TUG) and Habitual Gait Speed (HGS).