Abstract: Electromyography (EMG) signals are becoming increasingly important in manyapplications, including clinical/biomedical, prosthesis or rehabilitation devices, humanmachine interactions, and more. However, noisy EMG signals are the major hurdles to beovercome in order to achieve improved performance in the above applications. Detection,processing and classification analysis in electromyography (EMG) is very desirable becauseit allows a more standardized and precise evaluation of the neurophysiological, rehabitationaland assistive technological findings. This paper reviews two prominent areas; first: thepre-processing method for eliminating possible artifacts via appropriate preparation at thetime of recording EMG signals, and second: a brief explanation of the different methodsfor processing and classifying EMG signals. This study then compares the numerousmethods of analyzing EMG signals, in terms of their performance. The crux of this paperis to review the most recent developments and research studies related to the issuesmentioned above.
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