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  1. Medical and Biological Engineering and Computing
  2. Medical and Biological Engineering and Computing : Volume 42
  3. Medical and Biological Engineering and Computing : Volume 42, Issue 4, July 2004
  4. Surface electromyogram signal modelling
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Medical and Biological Engineering and Computing : Volume 55
Medical and Biological Engineering and Computing : Volume 54
Medical and Biological Engineering and Computing : Volume 53
Medical and Biological Engineering and Computing : Volume 52
Medical and Biological Engineering and Computing : Volume 51
Medical and Biological Engineering and Computing : Volume 50
Medical and Biological Engineering and Computing : Volume 49
Medical and Biological Engineering and Computing : Volume 48
Medical and Biological Engineering and Computing : Volume 47
Medical and Biological Engineering and Computing : Volume 46
Medical and Biological Engineering and Computing : Volume 45
Medical and Biological Engineering and Computing : Volume 44
Medical and Biological Engineering and Computing : Volume 43
Medical and Biological Engineering and Computing : Volume 42
Medical and Biological Engineering and Computing : Volume 42, Issue 6, November 2004
Medical and Biological Engineering and Computing : Volume 42, Issue 5, September 2004
Medical and Biological Engineering and Computing : Volume 42, Issue 4, July 2004
The European project ‘Neuromuscular assessment in the elderly worker’ (NEW): Achievements in electromyogram signal acquisition, modelling and processing
Methods for estimating muscle fibre conduction velocity from surface electromyographic signals
Surface electromyogram signal modelling
Sixty-four channel wearable acquisition system for long-term surface electromyogram recording with electrode arrays
Advances in surface electromyographic signal simulation with analytical and numerical descriptions of the volume conductor
Influence of muscle fibre shortening on estimates of conduction velocity and spectral frequencies from surface electromyographic signals
Correlation-based decomposition of surface electromyograms at low contraction forces
Non-invasive assessment of single motor unit mechanomyographic response and twitch force by spike-triggered averaging
Effects of electrode dislocation on electromyographic activity and relative rest time: Effectiveness of compensation by a normalisation procedure
Effect of flow disturbances remaining at the beginning of diastole on intraventricular diastolic flow and colour M-mode Doppler echocardiograms
Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings
Reducing power line interference in digitised electromyogram recordings by spectrum interpolation
Spatial filters based on independent component analysis for magnetic noise reduction in the magnetocardiogram
Indentation test of soft tissues with curved substrates: A finite element study
Biomechanical modelling of growth modulation following rib shortening or lengthening in adolescent idiopathic scoliosis
Single-trabecula building block for large-scale finite element models of cancellous bone
Influence of electrode impedance on threshold voltage for transcranial electrical stimulation in motor evoked potential monitoring
Analysis of auditory evoked potential parameters in the presence of radiofrequency fields using a support vector machines method
Method for the deconvolution of auditory steady-state responses
Medical and Biological Engineering and Computing : Volume 42, Issue 3, May 2004
Medical and Biological Engineering and Computing : Volume 42, Issue 2, March 2004
Medical and Biological Engineering and Computing : Volume 42, Issue 1, January 2004
Medical and Biological Engineering and Computing : Volume 41
Medical and Biological Engineering and Computing : Volume 40
Medical and Biological Engineering and Computing : Volume 39
Medical and Biological Engineering and Computing : Volume 38
Medical and Biological Engineering and Computing : Volume 37
Medical and Biological Engineering and Computing : Volume 36
Medical and Biological Engineering and Computing : Volume 35

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Single motor unit analysis from spatially filtered surface electromyogram signals. Part I: Spatial selectivity

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Surface electromyogram signal modelling

Content Provider SpringerLink
Author McGill, K. C.
Copyright Year 2004
Abstract The paper reviews the fundamental components of stochastic and motorunit-based models of the surface electromyogram (SEMG). Stochastic models used in ergonomics and kinesiology consider the SEMG to be a stochastic process whose amplitude is related to the level of muscle activation and whose power spectral density reflects muscle conduction velocity. Motor-unit-based models for describing the spatio-temporal distribution of individual motor-unit action potentials throughout the limb are quite robust, making it possible to extract precise information about motor-unit architecture from SEMG signals recorded by multi-electrode arrays. Motor-unit-based models have not yet been proven as successful, however, for extracting information about recruitment and firing rates throughout the full range of contraction. The relationship between SEMG and force during natural dynamic movements is much too complex to model in terms of single motor units.
Starting Page 446
Ending Page 454
Page Count 9
File Format PDF
ISSN 01400118
Journal Medical and Biological Engineering and Computing
Volume Number 42
Issue Number 4
e-ISSN 17410444
Language English
Publisher Springer-Verlag
Publisher Date 2004-01-01
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Surface electromyography Muscle Motor-unit action potential Firing rate Recruitment Force Biomedical Engineering Human Physiology Imaging Radiology Computer Applications
Content Type Text
Resource Type Article
Subject Biomedical Engineering Computer Science Applications
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