Title : 
Biosignal quality analysis of surface EMG using a correlation coefficient test for normality
         
        
            Author : 
Fraser, Graham D. ; Chan, Adrian D. C. ; Green, James R. ; MacIsaac, Dawn T.
         
        
            Author_Institution : 
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
         
        
        
        
        
        
            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).
         
        
            Keywords : 
correlation methods; electrocardiography; electromyography; medical signal detection; medical signal processing; ECG; Pearson correlation coefficient; automatic rejection; automatic verification sEMG acquisition setups; biosignal quality analysis; contaminated sEMG signals; correlation coefficient testing; electrocardiogram interference; motion artifact; power line interference; signal-to-noise ratio; surface EMG signals; surface electromyography signals; Contamination; Correlation coefficient; Electrocardiography; Electromyography; Interference; Muscles; Signal to noise ratio; Gaussian; biomedical measurements; biosignal quality analysis; contamination; correlation coefficient; electromyography; myoelectric signal; noise;
         
        
        
        
            Conference_Titel : 
Medical Measurements and Applications Proceedings (MeMeA), 2013 IEEE International Symposium on
         
        
            Conference_Location : 
Gatineau, QC
         
        
            Print_ISBN : 
978-1-4673-5195-9
         
        
        
            DOI : 
10.1109/MeMeA.2013.6549735