Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Automatic decomposition electromyography (ADEMG): validation and normative data in brachial biceps.

K C McGill, L J Dorfman

    Electroencephalography and Clinical Neurophysiology
    |November 1, 1985
    PubMed
    Summary

    A new automatic method, ADEMG, efficiently decomposes EMG signals into motor unit action potentials (MUAPs). This method offers fast analysis and detailed MUAP properties for clinical applications.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Motor unit activity within the depth of the masseter characterized by an adapted scanning EMG technique.

    Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2016
    Same author

    Neuroradiologic correlates of cognitive impairment in adult Moyamoya disease.

    AJNR. American journal of neuroradiology·2011
    Same author

    Accuracy assessment of CKC high-density surface EMG decomposition in biceps femoris muscle.

    Journal of neural engineering·2011
    Same author

    Automatic decomposition of multichannel intramuscular EMG signals.

    Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology·2007
    Same author

    Surface electromyogram signal modelling.

    Medical & biological engineering & computing·2004
    Same author

    A model of the muscle action potential for describing the leading edge, terminal wave, and slow afterwave.

    IEEE transactions on bio-medical engineering·2002

    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Electromyography

    Background:

    • Electromyography (EMG) signal decomposition is crucial for understanding neuromuscular function.
    • Traditional methods for analyzing motor unit action potentials (MUAPs) can be time-consuming and limited in scope.

    Purpose of the Study:

    • To introduce and validate a novel, automated method (ADEMG) for decomposing EMG interference patterns.
    • To quantify configurational and firing properties of MUAPs efficiently.

    Main Methods:

    • ADEMG utilizes digital prefiltering, high-resolution waveform alignment, firing-time analysis, and interference-cancellation averaging.
    • Validation involved recruitment/derecruitment studies and single-fiber-triggered averaging.
    • Normative data were collected from brachial biceps MUAPs during isometric contractions.

    Related Experiment Videos

    Main Results:

    • ADEMG achieved 33-98% accuracy in identifying MUAP occurrences with a 90-second analysis time for a 10-second EMG epoch.
    • The method successfully analyzed both low- and high-threshold MUAPs during moderate contractions.
    • Normative data for 2000 MUAPs were obtained and contrasted with traditional analysis.

    Conclusions:

    • ADEMG provides a fast and efficient approach for EMG decomposition in clinical settings.
    • The method enhances data acquisition speed and processing capabilities.
    • ADEMG offers valuable MUAP firing-rate information, expanding diagnostic potential.