期刊
COMPUTERS IN BIOLOGY AND MEDICINE
卷 47, 期 -, 页码 93-103出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2014.01.013
关键词
Electromyography; Signal processing; Muscle activity detection; Muscle activation pattern; Periodic movements; Averaging; Kinesiology
Muscle coordination during periodic movements is often studied using the average envelope of the electromyographic (EMG) signal. We show that this method causes a loss of important information, and potentially gives rise to errors in analysis of muscle activity coordination. We created four simulated two-channel surface EMG signals, in order to compare the results of muscle onset/cessation detection, performed on the average EMG envelope and the EMG envelopes in every single movement cycle. Our results show that the common method using the average EMG envelope is unable to reveal certain important characteristics of the EMG signals, while the analysis performed on individual cycles accentuates this information. This ability was verified on 16-channel surface EMGs obtained during walking and cycling. By detecting muscle activity in individual movement cycles, we could observe fine changes in muscle coordination. Moreover, muscles with questionable reliability of activity detection were distinguished and highlighted in the presented summary figures. In the second part of the paper, our publicly available set of MATLAB files for surface EMG signal processing is described. (C) 2014 Elsevier Ltd. All rights reserved.
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