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The acceptance of hand prostheses strongly depends on their user-friendliness and functionality. Current prostheses are limited to a few movements and their operation is all but intuitive. The development of practically applicable multi-movement prostheses requires the combination of modern classification methods with novel techniques for manufacturing high precision sockets. In this paper, the authors introduce an approach for classifying EMG signals taken from forearm muscles using support vector machines. This classifier technique is used in an adaptive operation mode and customized to the amputee, which allows one to recognize eleven different hand movements with high accuracy. Then, they present a novel manufacturing technique for prosthesis sockets enabling a precise amputee-specific fitting and EMG sensor placement.
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