Grasping Pattern Recognition and Grasping Force Estimation For Prosthetic Hands

Human’s movement can be decoded by surface electromyography (EMG), and the prosthetic hand can be controlled freely through EMG signal. This paper proposes a grasping pattern and force synchronized decoding method for prosthetic hands. Considering pattern recognition and force estimation simultaneously, this paper analyzes whether different muscle contraction levels affect pattern recognition and whether different grasping modes have impact on force estimation, then proposes two schemes to complete EMG simultaneously decoding. Experiments compare the accuracy of the two methods. The results show that there is no much difference between two methods in force estimation, the former’s accuracy of pattern recognition is a little higher than the latter