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Since the 1970s, electromyographic control of a prosthetic device has been attempted in a number of different ways. It was only until recently, that the classification of electromyo- graphic signals was possible through the use of neural networks. With the advent of more advanced techniques like support vector machines this type of control is becoming more re- alistic. This would initiate a great step in the development of prosthetic devices. It would become possible for more advanced control of these devices with a more natural interface. This project focuses on the development of an electromyographic classification system on an embedded platform for the specific use of controlling a prosthetic device.

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