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Wavelet-based detection on MUAPs decomposed from sEMG under different levels of muscle isometric contraction
Li ZY(李自由)1,2; Ding QC(丁其川)1; Zhao XG(赵新刚)1; Han JD(韩建达)1; Liu GJ(刘光军)1,3
Department机器人学研究室
Conference Name2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
Conference DateDecember 5-8, 2017
Conference PlaceMacau, China
Author of SourceBeijing Institute of Technology ; City University of Hong Kong ; IEEE Robotics and Automation Society ; Shenzhen Academy of Robotics ; University of Hong Kong ; University of Macau
Source PublicationProceedings of the 2017 IEEE International Conference on Robotics and Biomimetics
PublisherIEEE
Publication PlaceNew York
2017
Pages965-970
Indexed ByEI
EI Accession number20182905561455
Contribution Rank1
ISBN978-1-5386-3741-8
KeywordEMG Decomposition Motor Units Action Potential Wavelet transform muscle contraction evaluation
AbstractDecomposition of EMG (electromyography), in which the MUAPs (Motor Units Action Potentials) are extracted from the original EMG signals, is a useful approach for evaluating the physiological properties of muscles and studying the neural mechanism of human motions. Existing decomposition methods usually extracted the MUAPs via the waveform matching between the detected spikes and MUAP templates. However, those methods always involve too many artificial parameters and have no generally mathematical expression, which make them inflexible in practical applications and also cause poor robustness under interference. With respect to the problem, in this paper, a wavelet-based decomposition method is proposed to detect the "true" MUAPs from sEMG. Two standard Gaussian wavelets are firstly defined as the basic MUAP expressions; then, wavelet transform is performed to describe scales and magnitudes of different MUAPs from different nerve fibers. Experiments were conducted to verify the performance of the proposed method, where MUAPs decomposed from sEMG under different levels of muscle contraction can be effectively detected by the method.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/22126
Collection机器人学研究室
Corresponding AuthorLi ZY(李自由)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.University of Chinese Academy of Sciences (UCAS), Beijing 100049, China
3.Department of Aerospace Engineering, Ryerson University, Toronto, ON, Canada
Recommended Citation
GB/T 7714
Li ZY,Ding QC,Zhao XG,et al. Wavelet-based detection on MUAPs decomposed from sEMG under different levels of muscle isometric contraction[C]//Beijing Institute of Technology, City University of Hong Kong, IEEE Robotics and Automation Society, Shenzhen Academy of Robotics, University of Hong Kong, University of Macau. New York:IEEE,2017:965-970.
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