DocumentCode :
613481
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
fYear :
2013
fDate :
4-5 May 2013
Firstpage :
196
Lastpage :
200
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;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Medical Measurements and Applications Proceedings (MeMeA), 2013 IEEE International Symposium on
Conference_Location :
Gatineau, QC
Print_ISBN :
978-1-4673-5195-9
Type :
conf
DOI :
10.1109/MeMeA.2013.6549735
Filename :
6549735
Link To Document :
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