Control of Virtual Prosthesis Based on Mechanomyogram Signal

A novel way was presented to drive a virtual hand by using mechanomyography(MMG) signal.The MMG signal of the hand open-grip motion is acquired from the forearm,and seven kinds of time-domain features were extracted.Linear discriminant analysis was used for hand motion modes recognition.The final classification accuracy of motion modes is(95.63±2.55)%.Motion recognition results were utilized to generate proper pulses to manipulate a virtual prosthesis.The results show that the MMG signal has high accuracy of judging movements,and provides basis for prosthetic control of using MMG signal.