Research On Prosthesis Control System Based On Mechanomyogram And Electromyography

The traditional prosthesis control methods and research trends in myoelectric prosthesis control were reviewed and their shortcomings were analyzed with the aim to creat the overall framework of prosthesis control based on Mechanomyography(EMG) pattern recognition. At the same time, the configuration, function and detailed realization of the framework was clearly described.An eight-channel singnal acquisition device was designed for Mechanomyography (MMG) and EMG signal amplifying and filtering, and the EMG signal acquisition programs were designed based on virtual instruments. The device contained the amplifier, high-pass filter, low-pass filter, notch filter and compensation circuit modules. The acquired EMG signals could be displayed in real time and stored in a computer.To improve the accuracy of classification of prosthesis control system, in this study, a prosthesis control system based on MMG and EMG was studied and developed by using a signal fusion method. Six channels of MMG and two channels of EMG were fused, and combined with linear discriminant analysis (LDA) algorithm based on pattern recognition, which were applied for the test of the classification precision of prosthesis control system.8 volunteers were enrolled in the test including four kinds of activities and static status through this system. The precision reached to 94.6%±1.3%, which is better than the accuracy when MMG signal (89.7%) or EMG signal (90.4%±1.5%) was adopted only. The results proved that the system could classify the prosthesis controlling action efficiently, and control the prosthesis independently. This prosthesis control system is expected to be applied to the disabilities with upper arm amputated in the near future.