Paper Title
Cross Correlation Analysis of Multichannel EMG Signals for Finger Movements

Abstract
Correlation analysis is a very powerful efficient and easy-to-apply tool for determining association between variables that can be very useful for investigating spatial and temporal relationship between time varying signals. In this paper, we have analyzed the cross correlation between different finger movements by extracting time domain features. Fifteen classes of movement data were segmented by overlapping windowing. Five time domain features were extracted to get necessary feature vectors for cross-correlation analysis. Correlation for different finger movements for all the time domain features was calculated. A high (0.8) value of the correlation coefficient was found among different trials from same subject and low (0.39) value was found between different finger movements for every subjects. Keywords - Correlation, Features, Muscle, EMG, Analysis.