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This paper presents two methods for the classification of six different hand motions based on the analysis of the transient state of surface multichannel electromyographic signals recorded from 10 normally limbed subjects. The signals were classified using the coefficients extracted from a discrete wavelet transform analysis. While the first method uses a feature vector based on the variance of the...
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