Your browser doesn't support javascript.
loading
Analysis of motor unit spike trains estimated from high-density surface electromyography is highly reliable across operators.
Hug, François; Avrillon, Simon; Del Vecchio, Alessandro; Casolo, Andrea; Ibanez, Jaime; Nuccio, Stefano; Rossato, Julien; Holobar, Ales; Farina, Dario.
Afiliação
  • Hug F; Nantes University, Laboratory "Movement, Interactions, Performance" (EA 4334), Nantes, France; The University of Queensland, NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury and Health, School of Health and Rehabilitation Sciences, Brisbane, Australia; Institut Universitaire de Fr
  • Avrillon S; Legs Walking AbilityLab, Shirley Ryan AbilityLab, Chicago, IL, USA; Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, USA.
  • Del Vecchio A; Department of Artificial Intelligence in Biomedical Engineering, Faculty of Engineering, Friedrich-Alexander University, Erlangen-Nuremberg, 91052 Erlangen, Germany.
  • Casolo A; Department of Biomedical Sciences, University of Padova, Padua, Italy.
  • Ibanez J; Department of Bioengineering, Faculty of Engineering, Imperial College London, UK; Department of Clinical and Movement Disorders, Institute of Neurology, University College London, London WC1N 3BG, UK.
  • Nuccio S; Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Rome, Italy.
  • Rossato J; Nantes University, Laboratory "Movement, Interactions, Performance" (EA 4334), Nantes, France.
  • Holobar A; Faculty of Electrical Engineering and Computer Science, University of Maribor, Slovenia.
  • Farina D; Department of Bioengineering, Faculty of Engineering, Imperial College London, UK.
J Electromyogr Kinesiol ; 58: 102548, 2021 Jun.
Article em En | MEDLINE | ID: mdl-33838590
ABSTRACT
There is a growing interest in decomposing high-density surface electromyography (HDsEMG) into motor unit spike trains to improve knowledge on the neural control of muscle contraction. However, the reliability of decomposition approaches is sometimes questioned, especially because they require manual editing of the outputs. We aimed to assess the inter-operator reliability of the identification of motor unit spike trains. Eight operators with varying experience in HDsEMG decomposition were provided with the same data extracted using the convolutive kernel compensation method. They were asked to manually edit them following established procedures. Data included signals from three lower leg muscles and different submaximal intensities. After manual analysis, 126 ± 5 motor units were retained (range across operators 119-134). A total of 3380 rate of agreement values were calculated (28 pairwise comparisons × 11 contractions/muscles × 4-28 motor units). The median rate of agreement value was 99.6%. Inter-operator reliability was excellent for both mean discharge rate and time at recruitment (intraclass correlation coefficient > 0.99). These results show that when provided with the same decomposed data and the same basic instructions, operators converge toward almost identical results. Our data have been made available so that they can be used for training new operators.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Músculo Esquelético / Potencial Evocado Motor / Eletromiografia Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Músculo Esquelético / Potencial Evocado Motor / Eletromiografia Idioma: En Ano de publicação: 2021 Tipo de documento: Article