Activity analysis, fall detection and risk assessment systems and methods

Patent metadata

Field	Value
Publication number	US-10080513-B2
Application number	US-201715424375-A
Country	US
Kind code	B2
Filing date	Feb 3, 2017
Priority date	Apr 27, 2012
Publication date	Sep 25, 2018
Grant date	Sep 25, 2018

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.

First claim

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 moving within an observation 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, the three-dimensional data object representative of the person within the observation environment;
tracking, by the at least one processor, the three-dimensional data object over a plurality of frames of the depth images data; and
determining, by the at least one processor, that the person is walking within the observation environment, wherein the determining the person is walking comprises:
determining, by the at least one processor, a speed for the tracked three-dimensional data object over a time frame;
comparing, by the at least one processor, the determined speed with a speed threshold; and
stipulating the person to be walking wherein the determined speed is greater than the speed threshold;

assigning, by the at least one processor, a state indicative of the walking to the tracked three-dimensional data object;
then, once the person has been determined to be walking and the tracked three-dimensional object has been assigned a state indicative of walking:
determining, by the at least one processor, a walk straightness for the tracked three-dimensional data object;
determining, by the at least one processor, a walk length for the tracked three-dimensional data object;
determining, by the at least one processor, a walk duration for the tracked three-dimensional data object;
identifying and saving, by the at least one processor, the tracked three-dimensional data object in memory as a walking sequence when 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; and
determining a level of risk at which the person is of falling by 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.

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).

Assignees

• Univ Missouri

Inventors

• Stone Erik Edward
• Skubic Marjorie
• Rantz Marilyn
• Popescu Mihail

Classifications

• A61B5/0013

  Medical image data (A61B1/00011, A61B6/56, A61B8/56 take precedence) · CPC title

• G06T2207/10028

  Range image; Depth image; 3D point clouds · CPC title

• G06T2207/30241

  Trajectory · CPC title

• A61B5/112

  Gait analysis · CPC title

• A61B5/1128 Primary

  using image analysis (A61B5/1127 takes precedence) · CPC title