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

Travis W. Beck, Jason M. Defreitas, Joel T. Cramer, Jeffrey R. Stout

Research output: Contribution to journalArticle

9 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)353-361
Number of pages9
JournalPhysiological Measurement
Volume30
Issue number4
DOIs
StatePublished - 2009

Keywords

  • Amplitude
  • Electromyography
  • Filtering
  • Signal processing

ASJC Scopus subject areas

  • Biophysics
  • Physiology
  • Biomedical Engineering
  • Physiology (medical)

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