EMG FEATURE-SELECTION FOR MOVEMENT CONTROL OF A CYBERNETIC ARM

A variety of electromyographic (EMG) features have been evaluated for control of myoelectric cybernetic prosthetic arms. Movement class disc rimination, robustness, and computational complexity of these features have been investigated for different window sizes and noise levels. A n adaptive selection of window size for feature extraction has also be en developed and evaluated. The experiments were done on the data acqu ired from the residual biceps and triceps muscle of an above-elbow amp utee.