Neural network application to a discrimination system for EMG-controlled prostheses

A discrimination system using a neural network for the EMG controlled externally powered upper extremity prosthesis (EMG-C-EPUP) is proposed. The neural network is used in this system to learn the relation between the power spectrum of EMG signal analyzed by fast Fourier transform and the performance desired by the handicapped. The neural network has three layers: the input layer, the middle layer, and the output layer. It is shown that the discrimination system with the neural network could discriminate 7 performances from the EMG signals with the probability of 0.61 simultaneously.<>