Wavelet transform based EMG feature extraction and evaluation using scatter graphs

In the hand movement recognition system the most important step is feature extraction. Nowadays, the analysis of Electromyograhy signal using wavelet transform becoming the most powerful method. In this paper we have typically used the mathematical diagram tool i.e. scatter graph technique to evaluate the performance of EMG features. The EMG signal corresponding to the different hand movements and finger movements are considered. Various features that are widely used are extracted from the different wavelet coefficient. The graphs obtained for MAV(Mean Absolute Value) from the reconstructed coefficient shows the better performance.