Feature extraction of surface electromyography (sEMG) and signal processing technique in wavelet transform: A review

Abstract

Electromyography (EMG) is used to measure and keep information of the electrical activity that produced by muscles during contract and relax. The electrical activity is detected with the help of EMG electrodes. This review paper will focus on usage of common EMG signal recording techniques which is surface electromyography (sEMG). During sEMG recording, there are some recognized noises and motion artifact which will affect sEMG signal. Hence, several of signal processing had been implemented to remove the noises and acquired the important signals which contain useful information. sEMG feature extraction is highlighted part in signal processing which extract features in sEMG signal. In this paper, several of sEMG feature extraction that applied any of three main domains which are time domain (TD), frequency domain (FD) and time-frequency domain (TFD) had been analyzed and studied to determine the good feature extraction method.