Abstract
Surface electromyography (sEMG) is one type of bioelectrical signal produced by the human body. sEMG contains meaningful information associated with muscle activity and has numerous applications in motor control and neuromuscular physiology. sEMG signals can be used to identify the movement intention and evaluate the function status of muscles. sEMG is also applied in virtual reality with the advances of technology development. In this review paper, sEMG feature extraction methods and classification methods are summarized, and the future development is prospected.
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