In this paper, we attempted to evaluate the performance of an electromyography (EMG)-controlled 5-DOF prosthetic hand on ten transradial amputees. The proposed prosthesis is composed of a five-fingered hand, a passive wrist, and a customized socket for each subject. The EMG control methods included both a commonly used pattern recognition-based scheme (DD-SVM) and a novel digital encoding strategy (double-channel template matching (DCTM)). A virtual 3D hand platform was developed for training the subjects and rapidly testing the control methods. For each subject, the performance of the EMG control methods was firstly measured by off-line classification accuracy; then, according to the accuracy, a particular control method was selected and embedded in the EMG controller for further validation on ordinary daily life activities. Our experiments were conducted to test not only the hand's grasp ability but also other multifinger cooperation skills. The result indicated that the subjects of rich control experience can accomplish several intuitive motion control over their hands. However, the kinds of the motions and their relative recognition accuracy may depend on some individual differences, such as the amputation level, the activity of the residual nerve-muscle system, and the richness of control experience. Meanwhile, the proposed digital encoding method, DCTM, which only utilized two channels of EMG, was necessary for those amputees with few available control signals. This paper suggested that the EMG control method should be differently considered according to the particular condition of each subject.
['Dapeng Yang', 'Li Jiang', 'Qi Huang', 'Rongqiang Liu', 'Hong Liu']
Experimental Study of an EMG-Controlled 5-DOF Anthropomorphic Prosthetic Hand for Motion Restoration