Abstract
Human hand is very dexterous and has complicated functions. For amputees, it is significant to propose a myoelectric prosthetic hand which can recognize and accomplish various hand motions with reliable system. Therefore, this paper puts forward a mechanical hand with main joints individually powered by interference driven method. Driving program is redacted in Single-chip microcomputer (SCM), which controls the prosthetic hand to perform various movements according to different identification results. As for sEMG-Based identification of hand motion commands, we employed recognition algorithms using wavelet neural network (WNN) combined with discrete wavelet transform (DWT), recognizing six predefined kinds of hand motion with three sEMG sensors. The experimental results show that the developed myoelectric prosthetic hand can identify six kinds of human gestures and generate related hand motions, and the actual average accuracy rate is 91.44%.
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