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Tutorial on MUedit: An open-source software for identifying and analysing the discharge timing of motor units from electromyographic signals.
Avrillon, Simon; Hug, François; Baker, Stuart N; Gibbs, Ciara; Farina, Dario.
Afiliación
  • Avrillon S; Department of Bioengineering, Faculty of Engineering, Imperial College London, London W12 7TA, UK. Electronic address: s.avrillon@imperial.ac.uk.
  • Hug F; Université Côte d'Azur, LAMHESS, Nice 06200, France; The University of Queensland, School of Biomedical Sciences, St Lucia 4072, QLD, Australia.
  • Baker SN; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK.
  • Gibbs C; Department of Bioengineering, Faculty of Engineering, Imperial College London, London W12 7TA, UK.
  • Farina D; Department of Bioengineering, Faculty of Engineering, Imperial College London, London W12 7TA, UK. Electronic address: d.farina@imperial.ac.uk.
J Electromyogr Kinesiol ; 77: 102886, 2024 Aug.
Article en En | MEDLINE | ID: mdl-38761514
ABSTRACT
We introduce the open-source software MUedit and we describe its use for identifying the discharge timing of motor units from all types of electromyographic (EMG) signals recorded with multi-channel systems. MUedit performs EMG decomposition using a blind-source separation approach. Following this, users can display the estimated motor unit pulse trains and inspect the accuracy of the automatic detection of discharge times. When necessary, users can correct the automatic detection of discharge times and recalculate the motor unit pulse train with an updated separation vector. Here, we provide an open-source software and a tutorial that guides the user through (i) the parameters and steps of the decomposition algorithm, and (ii) the manual editing of motor unit pulse trains. Further, we provide simulated and experimental EMG signals recorded with grids of surface electrodes and intramuscular electrode arrays to benchmark the performance of MUedit. Finally, we discuss advantages and limitations of the blind-source separation approach for the study of motor unit behaviour during tonic muscle contractions.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos / Músculo Esquelético / Electromiografía / Neuronas Motoras / Contracción Muscular Idioma: En Revista: J Electromyogr Kinesiol Asunto de la revista: FISIOLOGIA Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos / Músculo Esquelético / Electromiografía / Neuronas Motoras / Contracción Muscular Idioma: En Revista: J Electromyogr Kinesiol Asunto de la revista: FISIOLOGIA Año: 2024 Tipo del documento: Article