Abstract
This paper presents a control method for prosthetic hand's grip force. Firstly, the correlated characters of the SEMG signal are calculated and input into the neural network in order to extract the estimation of muscle strength. Secondly, the estimation of muscle strength and the real-time prosthetic hand’s grip force are input into the designed fuzzy logic controller in order to adjust the motor speed, and indirectly control the grip force. This method could greatly reduce the individual difference of SEMG signal, make it can be used by Non-specific patient, and the experiment demonstrates that the control of prosthetic hand’s grip force is effective.
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