Literature DB >> 19242048

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

Travis W Beck1, Jason M DeFreitas, Joel T Cramer, Jeffrey R Stout.   

Abstract

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.

Mesh:

Year:  2009        PMID: 19242048     DOI: 10.1088/0967-3334/30/4/001

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  2 in total

1.  Filtering of surface EMG using ensemble empirical mode decomposition.

Authors:  Xu Zhang; Ping Zhou
Journal:  Med Eng Phys       Date:  2012-12-11       Impact factor: 2.242

2.  The effects of notch filtering on electrically evoked myoelectric signals and associated motor unit index estimates.

Authors:  Xiaoyan Li; William Z Rymer; Guanglin Li; Ping Zhou
Journal:  J Neuroeng Rehabil       Date:  2011-11-23       Impact factor: 4.262

  2 in total

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