Design and Implementation of an Intelligent Interface for Myoelectric Controlled Prosthesis
GRUPO DE INVESTIGACION Y DESARROLLO EN INSTRUMENTACION Y CONTROL (GIDIC) (COLOMBIA)
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In this paper, a discrimination system, using a neural network for electromyographic EMG externally controlled upper extremity prostheses is proposed. In this system, the Artificial Neural Network ANN is used to learn the relation between the power spectrum of EMG signal analyzed by Fast Fourier Transform FFT and the performance desired by handicapped people. The Neural Network can discriminate 7 performances of the EMG signals simultaneously. In order to prove the effectiveness of this system, experiments for discriminating the 7 arm performances of a healthy 23 year-old man, were carried out For real-time operation, a Digital Signal Processor ADSP-21061 operates over the resulting set of weights and maps the incoming signal to the stimuli control domain. Results show a highly accurate discrimination of the control signal over interference patterns.
- Medicine and Medical Research