Nonlinear spatial filtering of multichannel surface electromyogram signals during low force contractions

Ping Zhou*, Nina L. Suresh, Madeleine M. Lowery, William Z. Rymer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

This study introduces the application of nonlinear spatial filters to help identify single motor unit discharge from multiple channel surface electromyogram (EMG) signals during low force contractions. The nonlinear spatial filters simultaneously take into account the instantaneous amplitude and frequency information of a signal. This property was used to enhance motor unit action potentials (MUAPs) in the surface EMG record. The advantages of nonlinear spatial filtering for surface MUAP enhancement were investigated using both simulation and experimental approaches. The simulation results indicate that when compared with various linear spatial filters, nonlinear spatial filtering achieved higher SNR and higher kurtosis of the surface EMG distribution. Over a broad range of SNR and kurtosis levels for the input signal, nonlinear spatial filters achieved at least 32 times greater SNR and 11% higher kurtosis for correlated noise, and at least 15 times greater SNR and 1.7 times higher kurtosis for independent noise, across electrode array channels. The improvements offered by nonlinear spatial filters were further documented by applying them to experimental surface EMG array recordings. Compared with linear spatial filters, nonlinear spatial filters achieved at least nine times greater SNR and 25% higher kurtosis. It follows that nonlinear spatial filters represent a potentially useful supplement to linear spatial filters for detection of motor unit activity in surface EMG at low force contractions.

Original languageEnglish (US)
Article number4808156
Pages (from-to)1871-1879
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Volume56
Issue number7
DOIs
StatePublished - Jul 2009

Keywords

  • Low force contraction
  • Motor unit
  • Nonlinear spatial filter
  • Surface electromyogram (EMG)

ASJC Scopus subject areas

  • Biomedical Engineering

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