Document Detail


Filtering the surface EMG signal: Movement artifact and baseline noise contamination.
MedLine Citation:
PMID:  20206934     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The surface electromyographic (sEMG) signal that originates in the muscle is inevitably contaminated by various noise signals or artifacts that originate at the skin-electrode interface, in the electronics that amplifies the signals, and in external sources. Modern technology is substantially immune to some of these noises, but not to the baseline noise and the movement artifact noise. These noise sources have frequency spectra that contaminate the low-frequency part of the sEMG frequency spectrum. There are many factors which must be taken into consideration when determining the appropriate filter specifications to remove these artifacts; they include the muscle tested and type of contraction, the sensor configuration, and specific noise source. The band-pass determination is always a compromise between (a) reducing noise and artifact contamination, and (b) preserving the desired information from the sEMG signal. This study was designed to investigate the effects of mechanical perturbations and noise that are typically encountered during sEMG recordings in clinical and related applications. The analysis established the relationship between the attenuation rates of the movement artifact and the sEMG signal as a function of the filter band pass. When this relationship is combined with other considerations related to the informational content of the signal, the signal distortion of filters, and the kinds of artifacts evaluated in this study, a Butterworth filter with a corner frequency of 20 Hz and a slope of 12 dB/oct is recommended for general use. The results of this study are relevant to biomechanical and clinical applications where the measurements of body dynamics and kinematics may include artifact sources.
Authors:
Carlo J De Luca; L Donald Gilmore; Mikhail Kuznetsov; Serge H Roy
Related Documents :
8116284 - Antagonistic comparison of temporal frequency filter outputs as a basis for speed perce...
17945754 - Analysis of ambulatory ecg signal.
16764284 - Velocity selective filters recursively implemented in the spatiotemporal domain.
17690744 - A mathematical algorithm for ecg signal denoising using window analysis.
13680044 - Optic ataxia revisited: visually guided action versus immediate visuomotor control.
3627394 - Eeg fitting: a new method for numerical analysis of eeg.
Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't     Date:  2010-03-05
Journal Detail:
Title:  Journal of biomechanics     Volume:  43     ISSN:  1873-2380     ISO Abbreviation:  J Biomech     Publication Date:  2010 May 
Date Detail:
Created Date:  2010-05-10     Completed Date:  2010-08-20     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0157375     Medline TA:  J Biomech     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1573-9     Citation Subset:  IM    
Copyright Information:
Copyright 2010 Elsevier Ltd. All rights reserved.
Affiliation:
Delsys Inc., Boston MA, USA.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Adult
Algorithms
Artifacts*
Diagnosis, Computer-Assisted / methods*
Electromyography / methods*
Female
Humans
Male
Middle Aged
Movement / physiology*
Muscle Contraction / physiology*
Muscle, Skeletal / physiology*
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted*
Young Adult

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  The effect of three-dimensional geometrical changes during adolescent growth on the biomechanics of ...
Next Document:  A two-step EMG-and-optimization process to estimate muscle force during dynamic movement.