Development of a myoelectric discrimination system for a multi-degree prosthetic hand

Abstract

A multiple degrees of freedom prosthetic hand, NTU Hand, was developed in our laboratory. The paper focuses on the development of a myoelectric discrimination system for a multi-degree prosthetic hand. The discrimination system uses two surface electrodes to acquire the electromyography (EMG) signal from the flexor digitorum superficialis muscle and the extensor pollicis brevis muscle. Since eight types of hand movements, such as three-jaw chuck, lateral hand, hook grasp, power grasp, cylindrical grasp, centralized grip, flattened hand and wrist flexion are often used in daily life, they are used as key movements in the discrimination system. In order to distinguish those hand movements, the techniques of variance, bias zero-crossings, autoregressive model and spectral estimation are employed for preprocessing of features. Then, an error backpropagation neural network is applied to discriminate among the feature sets. Finally, an analysis interface system based on a PC environment is constructed to verify the idea. Besides, a 3-D graphic interface program based on the programmer's hierarchical interactive graphic system (PHIGS) is applied to simulate the prosthetic movement of the NTU hand. The discrimination system can achieve a success rate of 85% for off-line test and of 71% for online test.