Advance in Human Motion Intention Recognition Based on Surface Electromyography (review)
10.3969/j.issn.1006-9771.2021.05.013
- VernacularTitle:基于表面肌电图的人体运动意图识别研究进展
- Author:
Meng-lin CAO
1
;
Yu-hao CHEN
1
;
Jue WANG
1
;
Tian LIU
1
Author Information
1. The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitaion Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- Publication Type:Research Article
- Keywords:
rehabilitation robot;
human-machine interaction;
surface electromyography;
motion intention recognition;
review
- From:
Chinese Journal of Rehabilitation Theory and Practice
2021;27(5):595-603
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To summarize the methods and results of human motion intention recognition based on the surface electromyography. Methods:Literatures were retrieved and reviewed from the databases of PubMed, Web of Science, CNKI, Wanfang and VIP until December, 2020. The experimental researches about human motion intention recognition based on surface electromyography were summarized. Results:The methods of motion intention recognition were divided into three models: musculoskeletal model, traditional machine learning model and deep learning model. Conclusion:It is difficult to fully estimate human motion intention using surface electromyography in a single way. More researches are needed to develop more accurate and real-time human motion intention recognition methods.
