CleanEMG--power line interference estimation in sEMG using an adaptive least squares algorithm

G D Fraser; A D C Chan; J R Green; N Abser; D MacIsaac

doi:10.1109/IEMBS.2011.6091958

CleanEMG--power line interference estimation in sEMG using an adaptive least squares algorithm

Annu Int Conf IEEE Eng Med Biol Soc. 2011:2011:7941-4. doi: 10.1109/IEMBS.2011.6091958.

Authors

G D Fraser¹, A D C Chan, J R Green, N Abser, D MacIsaac

Affiliation

¹ Department of Systems & Computer Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, ON, Canada.

PMID: 22256182
DOI: 10.1109/IEMBS.2011.6091958

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).

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Artifacts*
Computer Simulation
Electromyography / methods*
Humans
Least-Squares Analysis
Signal-To-Noise Ratio
Surface Properties