Open AccessVision skeleton trajectory based motion assessment system for healthcare rehabilitation
Author(s) -
Shi Qinghongya,
Zhang HongBo,
Dong LiJia,
Lei Qing,
Hsiao TsungChih
Publication year - 2020
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.1316
Subject(s) - trajectory , rehabilitation , motion (physics) , physical medicine and rehabilitation , computer science , skeleton (computer programming) , health care , computer vision , artificial intelligence , medicine , physical therapy , political science , physics , astronomy , law , programming language
Most existing methods of motion assessment system used the contact sensor, infrared sensor, and depth sensor, and few works provided the solution of digital camera. To solve this problem, the authors propose a new motion assessment system based on light camera. In this work, the motion assessment was regarded as pattern regression problem of skeleton joint trajectory. Firstly, the system uses the camera to capture the image sequences. The pose estimation method is used to obtain body skeleton from image. Secondly, due to the difference of motion frequency of each person, the length of the image sequences is different and the length of each joint trajectory also will be different. Fourier transform is applied to normalise the trajectory and use the coefficients of Fourier transform as the joint trajectory feature. Finally, the regression model is built to assess the motion quality. Some experimental results and discussion on action video data are used to verify the effectiveness of the system.