A review on multi-modal human motion representation recognition and its application in orthopedic rehabilitation training.
10.7507/1001-5515.201906053
- Author:
Mengmeng XING
1
;
Guohui WEI
1
;
Jing LIU
1
;
Junzhong ZHANG
1
;
Feng YANG
1
;
Hui CAO
1
Author Information
1. School of Science and technology, Shandong University of Traditional Chinese Medicine, Jinan 250355, P.R.China.
- Publication Type:Journal Article
- Keywords:
action capture;
action feature extraction;
action recognition;
deep learning;
orthopedic rehabilitation training
- From:
Journal of Biomedical Engineering
2020;37(1):174-178
- CountryChina
- Language:Chinese
-
Abstract:
Human motion recognition (HAR) is the technological base of intelligent medical treatment, sports training, video monitoring and many other fields, and it has been widely concerned by all walks of life. This paper summarized the progress and significance of HAR research, which includes two processes: action capture and action classification based on deep learning. Firstly, the paper introduced in detail three mainstream methods of action capture: video-based, depth camera-based and inertial sensor-based. The commonly used action data sets were also listed. Secondly, the realization of HAR based on deep learning was described in two aspects, including automatic feature extraction and multi-modal feature fusion. The realization of training monitoring and simulative training with HAR in orthopedic rehabilitation training was also introduced. Finally, it discussed precise motion capture and multi-modal feature fusion of HAR, as well as the key points and difficulties of HAR application in orthopedic rehabilitation training. This article summarized the above contents to quickly guide researchers to understand the current status of HAR research and its application in orthopedic rehabilitation training.
