Biosignal quality analysis of surface EMG using a correlation coefficient test for normality

Abstract

A correlation test of normality is applied to surface electromyography (sEMG) signals to detect and quantify contaminants. Three contaminants were examined: power line interference, motion artifact, and electrocardiogram (ECG) interference. sEMG data from both simulations and human subjects were artificially contaminated at various signal-to-noise ratios (SNR). For each contaminant, lower SNR values were associated with a lower Pearson correlation coefficient; however, the value of the Pearson correlation coefficient did not correspond to the same SNR across contaminant types. The correlation test of normality can be a useful method for detecting contaminants in sEMG, when the type of contaminant is unknown (e.g., for automatic verification sEMG acquisition setups or automatic rejection of contaminated sEMG signals).