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Martinez-Valdes E, Enoka RM, Holobar A, McGill K, Farina D, Besomi M, Hug F, Falla D, Carson RG, Clancy EA, Disselhorst-Klug C, van Dieën JH, Tucker K, Gandevia S, Lowery M, Søgaard K, Besier T, Merletti R, Kiernan MC, Rothwell JC, Perreault E, Hodges PW. Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix. J Electromyogr Kinesiol 2023; 68:102726. [PMID: 36571885 DOI: 10.1016/j.jelekin.2022.102726] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/16/2022] [Accepted: 11/16/2022] [Indexed: 11/29/2022] Open
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.
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Affiliation(s)
- Eduardo Martinez-Valdes
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, UK
| | - Roger M Enoka
- Department of Integrative Physiology, University of Colorado Boulder, CO, USA
| | - Aleš Holobar
- Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, Maribor, Slovenia
| | | | - Dario Farina
- Department of Bioengineering, Imperial College London, London, UK
| | - Manuela Besomi
- School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia; School of Biomedical Sciences, The University of Queensland, Brisbane, Australia
| | - François Hug
- School of Biomedical Sciences, The University of Queensland, Brisbane, Australia; LAMHESS, Université Côte d'Azur, Nice, France; Institut Universitaire de France (IUF), Paris, France
| | - Deborah Falla
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, UK
| | - Richard G Carson
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland; School of Psychology, Queen's University Belfast, Belfast, UK; School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, Australia
| | | | - Catherine Disselhorst-Klug
- Department of Rehabilitation and Prevention Engineering, Institute of Applied Medical Engineering, RWTH Aachen University, Aachen, Germany
| | - Jaap H van Dieën
- Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | - Kylie Tucker
- School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia; School of Biomedical Sciences, The University of Queensland, Brisbane, Australia
| | - Simon Gandevia
- Neuroscience Research Australia, University of New South Wales, Sydney, Australia
| | - Madeleine Lowery
- School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin, Ireland
| | - Karen Søgaard
- Department of Clinical Research and Department of Sports Sciences and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Thor Besier
- Auckland Bioengineering Institute and Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Roberto Merletti
- LISiN, Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy
| | - Matthew C Kiernan
- Brain and Mind Centre, University of Sydney, Sydney, Australia Department of Neurology, Royal Prince Alfred Hospital, Sydney, Australia
| | - John C Rothwell
- Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, UK
| | - Eric Perreault
- Northwestern University, Evanston, IL, USA; Shirley Ryan AbilityLab, Chicago, IL, USA
| | - Paul W Hodges
- School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia.
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Finsen L, Søgaard K, Graven-Nielsen T, Christensen H. Activity patterns of wrist extensor muscles during wrist extensions and deviations. Muscle Nerve 2004; 31:242-51. [PMID: 15543552 DOI: 10.1002/mus.20237] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Wrist extensor muscles are prone to certain focal musculoskeletal disorders for which the activation pattern of the extensor carpi radialis (ECR) and ulnaris (ECU) muscles may be important risk factors. Surface and intramuscular EMG of these muscles were recorded during isometric low-force wrist extension in semipronation and pronation as well as for ulnar/radial deviation, and were analyzed using root mean square (RMS) and decomposition methods. Despite shorter ECR length at semipronation, higher amplitudes of intramuscular EMG and of motor unit action potentials (MUAPs) were found in pronation than in semipronation. However, these changes were not detectable in the surface EMG. Higher ECR activity levels were also found during wrist extension compared to ulnar/radial deviation, and differences in the motor unit (MU) properties were found during ulnar deviation compared to radial deviation and extension. Remarkably, the MUAPs of ECR were almost twice as large as those of the ECU. Overall, the ECR muscle did not respond as predicted from biomechanical considerations, and in general activity level was higher than expected. This may partly explain why the tendon of the ECR often is associated with lateral epicondylitis.
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Affiliation(s)
- L Finsen
- Department of Physiology, National Institute of Occupational Health, Lersø Parkalle 105, DK-2100 Copenhagen, Denmark
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