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Recognition of palm finger movements on the basis of EMG signals with the application of wavelets

Krysztoforski K., Wolczowski A., Będziński R., Helt K.

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

2004

Vol. 8, No 2

269-280

The paper describes an EMG signal analysis based on the wavelet transform, applied for the hand prosthesis control. Signal features are represented by wavelet coefficients. A cross-validation method is applied for the feature selection process. The classification algorithm uses multistage recognition. The information about finger posture provided by a data glove is recorded concurrently with forearm EMG signals. The acquired data are used to train the classification algorithm.

A wavelet approach to signal discrimination

Helt K.

Journal of Applied Computer Science

2003

Vol. 11, nr 2

19-29

In this paper, a multi-stage wavelet approach to a problem of signal discrimination is presented. This method uses wavelet expansions of signals. It allows decomposing a highly dimensional classification problem into a few ones of smaller dimensions. A general scheme and implementation to discrimination of ECG signals is given. In order to adapt the general scheme to this particular problem a cross-validation technique is used.