Title :
CleanEMG — Power line interference estimation in sEMG using an adaptive least squares algorithm
Author :
Fraser, G.D. ; Chan, A.D.C. ; Green, J.R. ; Abser, N. ; MacIsaac, D.
Author_Institution :
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
fDate :
Aug. 30 2011-Sept. 3 2011
Abstract :
This paper presents an adaptive least squares algorithm for estimating the power line interference in surface electromyography (sEMG) signals. The algorithm estimates the power line interference, without the need for a reference input. Power line interference can be removed by subtracting the estimate from the original sEMG signal. The algorithm is evaluated with simulated sEMG based on its ability to accurately estimate power line interference at different frequencies and at various signal-to-noise ratios. Power line estimates produced by the algorithm are accurate for signal-to-noise ratios below 15 dB (SNR estimation error at 15 dB is 14.7995 dB + 1.6547 dB).
Keywords :
electromyography; estimation theory; interference (signal); least squares approximations; medical signal processing; power cables; CleanEMG; adaptive least squares algorithm; power line interference estimation; signal-to-noise ratios; surface electromyography; Adaptive algorithms; Electromyography; Frequency estimation; Interference; Least squares approximation; Signal to noise ratio; Algorithms; Artifacts; Computer Simulation; Electromyography; Humans; Least-Squares Analysis; Signal-To-Noise Ratio; Surface Properties;
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2011.6091958
