This study proposes a method to control a prosthetic hand by EMG signals based on muscle synergies. The muscle synergy model suggests a framework to transform commands of the central nervous system to a set of complex muscular movements. Using this method, we have tried to realize the proportional control of multiple degrees of freedom (DOF). This study focuses on controlling four kinds of hand/wrist movements of the prosthesis: open, close, pronate, and supinate. The nonnegative matrix factorization (NMF) algorithm is used to map muscle activities into these four movements through the calculation of a muscle synergy matrix.
An EMG feature selection process along with a control scheme has been added, which smooths the output thereby stabilizing the movements. Ten healthy subjects performed an online experiment comprised of two tests: 1) proportional control on single DOF, and 2) simultaneous control of multiple DOFs. The results indicate that fluid hand/wrist movements could be estimated from EMG. The average R2 values achieved by all subjects for the single-DOF test and the multiple-DOF test are 0.97 and 0.93, respectively.