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A comparison of adaptive and notch filtering for removing electromagnetic noise from monopolar surface electromyographic signals

Travis W Beck1,3, Jason M DeFreitas1, Joel T Cramer1 and Jeffrey R Stout2

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The purpose of this study was to compare the monopolar electromyographic (EMG) amplitude versus isometric force relationships from three signal processing methods (raw versus notch filtering versus adaptive filtering). Seventeen healthy subjects (mean ± SD age = 24.6 ± 4.3 yr) performed incremental isometric muscle actions of the dominant leg extensors in 10% increments from 10% to 100% of the maximum voluntary contraction (MVC). During each muscle action, a monopolar surface EMG signal was recorded from the vastus lateralis and processed with the three signal processing methods. The linear slope coefficients for the EMG amplitude versus isometric force relationships were equivalent for the three signal processing methods and correlated (r = 0.997–0.999). However, the mean amplitude values for the notch-filtered signals were less than those for the raw and adaptive-filtered signals. Thus, adaptive filtering may be the best method for removing electromagnetic noise from monopolar surface EMG signals.


PACS

87.85.Ng Biological signal processing

87.19.Ff Muscles

87.19.R- Mechanical and electrical properties of tissues and organs

87.19.L- Neuroscience

Subjects

Medical physics

Biological physics

Dates

Issue 4 (April 2009)

Received 24 November 2008, accepted for publication 3 February 2009

Published 25 February 2009



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