Automatic Evaluation of Trunk Function Tests and Joint Movement Tests for Stroke Impairment Assessment Set by Using Depth Sensor

Abstract

In the field of rehabilitation, Stroke Impairment Assessment Set (SIAS) is used to evaluate the body dysfunctions for the post-stroke that is the disease of the brain. We have been developing automatic evaluation systems for the motor dysfunction in SIAS by using the detected joints of the body by using depth sensor. However, the joint detection is a specific function to Kinect and is not always possible for other depth sensors. Moreover, even when using Kinect, the positions of the joints are not correctly estimated when observed from the backward or with irregular poses. Thus, it is often inevitable to analyze the body poses from depth data directly. In this study, we directly apply depth data to the trunk function tests and joint movements of SIAS. The measuring method of angles from the raw depth data will be proposed, and the results are compared to the traditional test method of SIAS.