Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix

Eduardo Martinez-Valdes, Roger M. Enoka, Aleš Holobar, Kevin McGill, Dario Farina, Manuela Besomi, François Hug, Deborah Falla, Richard G. Carson, Edward A. Clancy, Catherine Disselhorst-Klug, Jaap H. van Dieën, Kylie Tucker, Simon Gandevia, Madeleine Lowery, Karen Søgaard, Thor Besier, Roberto Merletti, Matthew C. Kiernan, John C. RothwellEric Perreault, Paul W. Hodges*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.

Original languageEnglish (US)
Article number102726
JournalJournal of Electromyography and Kinesiology
Volume68
DOIs
StatePublished - Feb 2023

Keywords

  • High-density surface electromyography
  • Intramuscular electromyography
  • Motor neuron
  • Motor unit

ASJC Scopus subject areas

  • Clinical Neurology
  • Biophysics
  • Neuroscience (miscellaneous)

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