IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i4p2001-d501829.html
   My bibliography  Save this article

A Neurophysiological Pattern as a Precursor of Work-Related Musculoskeletal Disorders Using EEG Combined with EMG

Author

Listed:
  • Colince Meli Segning

    (Department of Applied Sciences, Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada
    Laboratoire de Recherche Biomécanique et Neurophysiologique en Réadaptation Neuro-Musculo-Squelettique ( Lab BioNR ), Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada)

  • Hassan Ezzaidi

    (Department of Applied Sciences, Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada)

  • Rubens A. da Silva

    (Laboratoire de Recherche Biomécanique et Neurophysiologique en Réadaptation Neuro-Musculo-Squelettique ( Lab BioNR ), Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada
    Department of Health Sciences, Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada)

  • Suzy Ngomo

    (Laboratoire de Recherche Biomécanique et Neurophysiologique en Réadaptation Neuro-Musculo-Squelettique ( Lab BioNR ), Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada
    Department of Health Sciences, Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada)

Abstract

We aimed to determine the neurophysiological pattern that is associated with the development of musculoskeletal pain that is induced by biomechanical constraints. Twelve (12) young healthy volunteers (two females) performed two experimental realistic manual tasks for 30 min each: (1) with the high risk of musculoskeletal pain development and (2) with low risk for pain development. During the tasks, synchronized electroencephalographic (EEG) and electromyography (EMG) signals data were collected, as well as pain scores. Subsequently, two main variables were computed from neurophysiological signals: (1) cortical inhibition as Task-Related Power Increase (TRPI) in beta EEG frequency band (β.TRPI) and (2) muscle variability as Coefficient of Variation (CoV) from EMG signals. A strong effect size was observed for pain measurement under the high risk condition during the last 5 min of the task execution; with muscle fatigue, because the CoV has decreased below 18%. An increase in cortical inhibition (β.TRPI >50%) was observed after the 5th min of the task in both experimental conditions. These results suggest the following neurophysiological pattern—β.TRPI ≥ 50% and CoV ≤ 18%—as a possible indicator to monitor the development of musculoskeletal pain in the shoulder in the context of repeated and prolonged exposure to manual tasks.

Suggested Citation

  • Colince Meli Segning & Hassan Ezzaidi & Rubens A. da Silva & Suzy Ngomo, 2021. "A Neurophysiological Pattern as a Precursor of Work-Related Musculoskeletal Disorders Using EEG Combined with EMG," IJERPH, MDPI, vol. 18(4), pages 1-17, February.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:4:p:2001-:d:501829
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/4/2001/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/4/2001/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Melissa Airem Cázares-Manríquez & Claudia Camargo-Wilson & Ricardo Vardasca & Jorge Luis García-Alcaraz & Jesús Everardo Olguín-Tiznado & Juan Andrés López-Barreras & Blanca Rosa García-Rivera, 2021. "Quantitative Models for Prediction of Cumulative Trauma Disorders Applied to the Maquiladora Industry," IJERPH, MDPI, vol. 18(7), pages 1-19, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:4:p:2001-:d:501829. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.