Abstract— In the last decades, the researchers of the human arm prosthesis are using different types of machine learning algorithms. This review article firstly gives a brief explanation about type of machine learning methods. Secondly, some recent applications of myoelectric control of human arm prosthesis by using machine learning algorithms are compared. This study presents two different comparisons based on feature extraction methods which are time series modeling and wavelet transform of EMG signal. Finally, of characterization of EMG for of human arm prosthesis have been and discussed.
Index Terms— Machine learning, characterization, EMG signal, prosthesis.
Bekir KARLIK is with the Department of Computer Engineering, Engineering Faculty, Selcuk University in Konya, Turkey (e-mail: bkarlik@selcuk.edu.tr).
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Cite: Bekir Karlık, " Machine Learning Algorithms for Characterization of EMG Signals," International Journal of Information and Electronics Engineering vol. 4, no. 3, pp. 189-194, 2014.
