Towards a Hand Gestures Recognition Using Weak and a Single-channel Surface Emg Signals
نویسنده
چکیده
This article presents a method to obtain a myoelectric control system for hand prosthesis with individual fingers, wrist flexion/extension and grasp movements, based on weak surface electromyogram (sEMG) recorded from the forearm, both able-bodied and amputees. This study aims to a reduced-channel scheme (a single sEMG channel) for hand patterns discrimination. A combination of commonly used features in the Frequency Domain (FD) and Time Domain (TD) with the analysis fractal was studied to obtain the best set of features. The results were validated with different classifiers showing the high performance of the method, above 90%.
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تاریخ انتشار 2014