Research on surface electromyographic signal decomposition based on the level of contraction force.
- Author:
Hao DENG
1
;
Xiang CHEN
;
Bo YAO
;
Zhi LOU
;
Jihai YANG
Author Information
1. Department of Electronic Science & Technology, University of Science & Technology of China, Hefei 230027, China.
- Publication Type:Journal Article
- MeSH:
Action Potentials;
Algorithms;
Electromyography;
methods;
Humans;
Muscle Contraction;
physiology;
Muscle, Skeletal;
physiology;
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2012;29(6):1046-1077
- CountryChina
- Language:Chinese
-
Abstract:
Aiming at the difficulty of surface electromyography (SEMG) signal decomposition, we in this paper proposed a method of gradual processing based on contraction force level of muscle. At first, SEMG signals were recorded at different levels of muscle contraction force. Then, the SEMG data recorded at minimum level of contraction force were decomposed adopting the conventional methods. Further, the data at higher level of contraction force was decomposed using the templates and inter-pulse interval (IPI) information resulted from the previous composition performed at lower level of contraction force. Such procedure was iteratively performed level by level until the SEMG data at the maximal level of contraction force were successfully decomposed. The experimental results showed that the proposed method was effective in decomposing SEMG data, offering a valuable solution to the difficulty in obtaining templates at relatively high level of muscle contraction force. The complexity of SEMG decomposition in the case of high level of contraction force could also be reduced to a certain extent by using the proposed method.
