RECOGNITION OF PALM FINGER MOVEMENTS ON THE BASIS OF EMG SIGNALS WITH THE APPLICATION OF WAVELETS

Abstract

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.