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• W2156982852 abstract "One of the main problems in developing active prosthesis is how to control them in a natural way. In order to increase the effectiveness of hand prostheses there is a need in better exploiting electromyography EMG signals. After an analysis of the movements necessary for grasping, we individuated five movements for the wrist-hand mobility. Then we designed the basic electronics and software for the acquisition and the analysis of the EMG signals. We built a small size electronic device capable of registering them that can be integrated into a hand prosthesis. Among all the numerous muscles that move the fingers, we have chosen the ones in the forearm and positioned only two electrodes. To recognize the operation, we developed a classification system, using a novel integration of Artificial Neural Networks ANN and wavelet features." @default.
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• W2156982852 date "2012-04-01" @default.
• W2156982852 modified "2023-10-18" @default.
• W2156982852 title "Acquisition and analysis of EMG signals to recognize multiple hand movements for prosthetic applications" @default.
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• W2156982852 doi "https://doi.org/10.3233/abb-2011-0024" @default.
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