Improving myoelectric signal classification using wavelet packets and principal components analysis

An accurate and computationally efficient means of classifying surface myoelectric signals has been the subject of considerable research effort in recent years. This work demonstrates how this may be achieved, using a wavelet packet based feature set in conjunction with principal components analysis.

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