An accurate and computationally efficient means of classifying surface myoelectric signal
patterns has been the subject of considerable research effort in recent years. Effective
feature extraction is crucial to reliable classification and, in the quest to improve the accuracy
of transient myoelectric signal pattern classification, an ensemble of time-frequency based
representations are proposed. It is shown that feature sets based upon the short-time Fourier
transform, the wavelet transform, and the wavelet packet transform provide an effective …