Journal article
Modeling nonlinear errors in surface electromyography due to baseline noise: A new methodology
Journal of biomechanics, Vol.44(1), pp.202-205
2011
DOI: 10.1016/j.jbiomech.2010.09.008
PMCID: PMC3003745
PMID: 20869716
Abstract
The surface electromyographic (EMG) signal is often contaminated by some degree of baseline noise. It is customary for scientists to subtract baseline noise from the measured EMG signal prior to further analyses based on the assumption that baseline noise adds linearly to the observed EMG signal. The stochastic nature of both the baseline and EMG signal, however, may invalidate this assumption. Alternately, “true” EMG signals may be either minimally or nonlinearly affected by baseline noise. This information is particularly relevant at low contraction intensities when signal-to-noise ratios (SNR) may be lowest. Thus, the purpose of this simulation study was to investigate the influence of varying levels of baseline noise (approximately 2–40% maximum EMG amplitude) on mean EMG burst amplitude and to assess the best means to account for signal noise. The simulations indicated baseline noise had minimal effects on mean EMG activity for maximum contractions, but increased nonlinearly with increasing noise levels and decreasing signal amplitudes. Thus, the simple baseline noise subtraction resulted in substantial error when estimating mean activity during low intensity EMG bursts. Conversely, correcting EMG signal as a nonlinear function of both baseline and measured signal amplitude provided highly accurate estimates of EMG amplitude. This novel nonlinear error modeling approach has potential implications for EMG signal processing, particularly when assessing co-activation of antagonist muscles or small amplitude contractions where the SNR can be low.
Details
- Title: Subtitle
- Modeling nonlinear errors in surface electromyography due to baseline noise: A new methodology
- Creators
- Laura Frey Law - Neuromuscular Biomechanics Laboratory, Graduate Program in Physical Therapy and Rehabilitation Science, University of Iowa, Iowa City, IA 52242-1190, USAChandramouli Krishnan - Searle Laboratory, Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, USAKeith Avin - Neuromuscular Biomechanics Laboratory, Graduate Program in Physical Therapy and Rehabilitation Science, University of Iowa, Iowa City, IA 52242-1190, USA
- Resource Type
- Journal article
- Publication Details
- Journal of biomechanics, Vol.44(1), pp.202-205
- DOI
- 10.1016/j.jbiomech.2010.09.008
- PMID
- 20869716
- PMCID
- PMC3003745
- NLM abbreviation
- J Biomech
- ISSN
- 0021-9290
- eISSN
- 1873-2380
- Publisher
- Elsevier Ltd
- Language
- English
- Date published
- 2011
- Academic Unit
- Nursing; Physical Therapy and Rehabilitation Science
- Record Identifier
- 9984047883102771
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