Gesture recognition method based on a single-channel sEMG envelope signal

Autor: Yansheng Wu, Shili Liang, Ling Zhang, Zongqian Chai, Chunlei Cao, Shuangwei Wang
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: EURASIP Journal on Wireless Communications and Networking, Vol 2018, Iss 1, Pp 1-8 (2018)
Druh dokumentu: article
ISSN: 1687-1499
89392795
DOI: 10.1186/s13638-018-1046-0
Popis: Abstract In the past, investigators tend to use multi-channel surface electromyography (sEMG) signal acquisition devices to improve the recognition accuracy for the study of gesture recognition systems based on sEMG. The disadvantages of the method are the increased complexity and the problems such as signal crosstalk. This paper explores a gesture recognition method based on a single-channel sEMG envelope signal feature in the time domain. First, we get the sEMG envelope signal by using a preprocessing circuit. Then, we use the improved method of valid activity segment extraction to find every valid activity segment and extract 15 features from every valid activity segment. Next, we calculate the absolute value of the correlation coefficient between each of the features and target values. After removing the feature with the smaller correlation coefficient, we reserve the 14 features. By the PCA dimensionality reduction algorithm, we transform the 14-dimensional feature into 2-dimensional feature space. Finally, we use the improved KNN algorithm and the soft margin SVM algorithm to complete the classification of five types of gestures. We obtain the gesture recognition rates of 75.8 and 79.4% by using the improved KNN algorithm and the soft margin SVM algorithm.
Databáze: Directory of Open Access Journals
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