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. Rothwell; Eric Perreault; Paul W. Hodges

doi:10.1016/j.jelekin.2022.102726

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 Journal › Article › Academic › peer-review

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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 language	English
Article number	102726
Pages (from-to)	1-14
Number of pages	14
Journal	Journal of Electromyography and Kinesiology
Volume	68
Early online date	28 Nov 2022
DOIs	https://doi.org/10.1016/j.jelekin.2022.102726
Publication status	Published - Feb 2023

Bibliographical note

Funding Information:
The CEDE group wishes to acknowledge the contribution of Prof. Dario G. Liebermann, the special editor for this series, for his critical assessment of the first version of this paper which substantially helped in refining it. We acknowledge the financial and intellectual support provided by the International Society of Electrophysiology and Kinesiology (ISEK) for the CEDE project.

Funding Information:
MML is supported by the European Research Council Grant (ERC-2014- CoG-646923_DBSModel). PWH is supported by an NHMRC Senior Principal Research Fellowship (APP1102905). MCK was supported by the NHMRC Program Grant (APP1132524), Partnership Project (APP1153439) and Practitioner Fellowship (APP1156093). AH is supported by Slovenian Research Agency (projects J2-1731 and L7-9421 and Program funding P2-0041). FH is supported by a fellowship from the Institut Universitaire de France (IUF). DF is supported by the European Research Council (ERC; 810346) and by the Royal Society (Wolfson Research Merit Award).

Publisher Copyright:
© 2022 Elsevier Ltd

Funding

The CEDE group wishes to acknowledge the contribution of Prof. Dario G. Liebermann, the special editor for this series, for his critical assessment of the first version of this paper which substantially helped in refining it. We acknowledge the financial and intellectual support provided by the International Society of Electrophysiology and Kinesiology (ISEK) for the CEDE project. MML is supported by the European Research Council Grant (ERC-2014- CoG-646923_DBSModel). PWH is supported by an NHMRC Senior Principal Research Fellowship (APP1102905). MCK was supported by the NHMRC Program Grant (APP1132524), Partnership Project (APP1153439) and Practitioner Fellowship (APP1156093). AH is supported by Slovenian Research Agency (projects J2-1731 and L7-9421 and Program funding P2-0041). FH is supported by a fellowship from the Institut Universitaire de France (IUF). DF is supported by the European Research Council (ERC; 810346) and by the Royal Society (Wolfson Research Merit Award).

Funders	Funder number
International Society of Electrophysiology and Kinesiology
European Research Council	ERC-2014- CoG-646923_DBSModel
European Research Council
National Health and Medical Research Council	APP1156093, APP1153439, APP1102905, APP1132524
National Health and Medical Research Council
Javna Agencija za Raziskovalno Dejavnost RS	L7-9421, J2-1731, P2-0041
Javna Agencija za Raziskovalno Dejavnost RS
Institut universitaire de France	810346
Institut universitaire de France
Royal Society of South Australia

Keywords

High-density surface electromyography
Intramuscular electromyography
Motor neuron
Motor unit

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10.1016/j.jelekin.2022.102726

Consensus for experimental design in electromyography (CEDE) projectFinal published version, 617 KBLicence: Article 25fa Dutch Copyright Act

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Martinez-Valdes, E., Enoka, R. M., Holobar, A., McGill, K., Farina, D., Besomi, M., Hug, F., Falla, D., Carson, R. G., Clancy, E. A., Disselhorst-Klug, C., van Dieën, J. H., Tucker, K., Gandevia, S., Lowery, M., Søgaard, K., Besier, T., Merletti, R., Kiernan, M. C., ... Hodges, P. W. (2023). Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix. Journal of Electromyography and Kinesiology, 68, 1-14. Article 102726. https://doi.org/10.1016/j.jelekin.2022.102726

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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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author = "Eduardo Martinez-Valdes and Enoka, {Roger M.} and Ale{\v s} Holobar and Kevin McGill and Dario Farina and Manuela Besomi and Fran{\c c}ois Hug and Deborah Falla and Carson, {Richard G.} and Clancy, {Edward A.} and Catherine Disselhorst-Klug and {van Die{\"e}n}, {Jaap H.} and Kylie Tucker and Simon Gandevia and Madeleine Lowery and Karen S{\o}gaard and Thor Besier and Roberto Merletti and Kiernan, {Matthew C.} and Rothwell, {John C.} and Eric Perreault and Hodges, {Paul W.}",

note = "Funding Information: The CEDE group wishes to acknowledge the contribution of Prof. Dario G. Liebermann, the special editor for this series, for his critical assessment of the first version of this paper which substantially helped in refining it. We acknowledge the financial and intellectual support provided by the International Society of Electrophysiology and Kinesiology (ISEK) for the CEDE project. Funding Information: MML is supported by the European Research Council Grant (ERC-2014- CoG-646923_DBSModel). PWH is supported by an NHMRC Senior Principal Research Fellowship (APP1102905). MCK was supported by the NHMRC Program Grant (APP1132524), Partnership Project (APP1153439) and Practitioner Fellowship (APP1156093). AH is supported by Slovenian Research Agency (projects J2-1731 and L7-9421 and Program funding P2-0041). FH is supported by a fellowship from the Institut Universitaire de France (IUF). DF is supported by the European Research Council (ERC; 810346) and by the Royal Society (Wolfson Research Merit Award). Publisher Copyright: {\textcopyright} 2022 Elsevier Ltd",

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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 2023, 'Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix', Journal of Electromyography and Kinesiology, vol. 68, 102726, pp. 1-14. https://doi.org/10.1016/j.jelekin.2022.102726

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AU - Martinez-Valdes, Eduardo

AU - Enoka, Roger M.

AU - Holobar, Aleš

AU - McGill, Kevin

AU - Farina, Dario

AU - Besomi, Manuela

AU - Hug, François

AU - Falla, Deborah

AU - Carson, Richard G.

AU - Clancy, Edward A.

AU - Disselhorst-Klug, Catherine

AU - van Dieën, Jaap H.

AU - Tucker, Kylie

AU - Gandevia, Simon

AU - Lowery, Madeleine

AU - Søgaard, Karen

AU - Besier, Thor

AU - Merletti, Roberto

AU - Kiernan, Matthew C.

AU - Rothwell, John C.

AU - Perreault, Eric

AU - Hodges, Paul W.

N1 - Funding Information: The CEDE group wishes to acknowledge the contribution of Prof. Dario G. Liebermann, the special editor for this series, for his critical assessment of the first version of this paper which substantially helped in refining it. We acknowledge the financial and intellectual support provided by the International Society of Electrophysiology and Kinesiology (ISEK) for the CEDE project. Funding Information: MML is supported by the European Research Council Grant (ERC-2014- CoG-646923_DBSModel). PWH is supported by an NHMRC Senior Principal Research Fellowship (APP1102905). MCK was supported by the NHMRC Program Grant (APP1132524), Partnership Project (APP1153439) and Practitioner Fellowship (APP1156093). AH is supported by Slovenian Research Agency (projects J2-1731 and L7-9421 and Program funding P2-0041). FH is supported by a fellowship from the Institut Universitaire de France (IUF). DF is supported by the European Research Council (ERC; 810346) and by the Royal Society (Wolfson Research Merit Award). Publisher Copyright: © 2022 Elsevier Ltd

PY - 2023/2

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N2 - 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.

AB - 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.

KW - High-density surface electromyography

KW - Intramuscular electromyography

KW - Motor neuron

KW - Motor unit

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

Abstract

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Keywords

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