期刊
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
卷 117, 期 2, 页码 247-256出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.cmpb.2014.06.013
关键词
Differencing technique; Dynamic motions; Electromyography (EMG); Muscle-computer interface; Non-stationary signal
类别
资金
- FT MSTIC University Joseph Fourier Grenoble 1 (TIGRE project)
- Lab Ex PERSYVAL-Lab - French program Investissement d'avenir [ANR-11-LABX-0025-01]
This paper demonstrates the utility of a differencing technique to transform surface EMG signals measured during both static and dynamic contractions such that they become more stationary. The technique was evaluated by three stationarity tests consisting of the variation of two statistical properties, i.e., mean and standard deviation, and the reverse arrangements test. As a result of the proposed technique, the first difference of EMG time series became more stationary compared to the original measured signal. Based on this finding, the performance of time-domain features extracted from raw and transformed EMG was investigated via an EMG classification problem (i.e., eight dynamic motions and four EMG channels) on data from 18 subjects. The results show that the classification accuracies of all features extracted from the transformed signals were higher than features extracted from the original signals for six different classifiers including quadratic discriminant analysis. On average, the proposed differencing technique improved classification accuracies by 2-8%. (C) 2014 Elsevier Ireland Ltd. All rights reserved.
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