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

fYear

2011

fDate

Aug. 30 2011-Sept. 3 2011

Firstpage

7941

Lastpage

7944

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE

Conference_Location

Boston, MA

ISSN

1557-170X

Print_ISBN

978-1-4244-4121-1

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2011.6091958

Filename

6091958