TY - JFULL AU - Farzaneh Akhavan Mahdavi and Siti Anom Ahmad and Mohd Hamiruce Marhaban and Mohammad-R. Akbarzadeh-T PY - 2013/3/ TI - The Utility of Wavelet Transform in Surface Electromyography Feature Extraction -A Comparative Study of Different Mother Wavelets T2 - International Journal of Biomedical and Biological Engineering SP - 106 EP - 112 VL - 7 SN - 1307-6892 UR - https://publications.waset.org/pdf/2502 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 74, 2013 N2 - Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements. ER -