High-density surface electromyography allows to identify risk conditions and people with and without low back pain during fatiguing frequency-dependent lifting activities

Tiwana Varrecchia, Alberto Ranavolo*, Giorgia Chini, Alessandro Marco De Nunzio, Francesco Draicchio, Eduardo Martinez-Valdes, Deborah Falla, Silvia Conforto

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Low back pain (LBP) is a leading cause of disability in the workplace, often caused by manually lifting of heavy loads. Instrumental-based assessment tools are used to quantitatively assess the biomechanical risk of lifting activities. This study aims to verify that, during the execution of fatiguing frequency-dependent lifting, high-density surface electromyography (HDsEMG) allows the discrimination of healthy controls (HC) versus people with LBP and biomechanical risk levels. Fifteen HC and eight people with LBP performed three lifting tasks with a progressively increasing lifting index, each lasting 15 min. Erector spinae (ES) activity was recorded using HDsEMG and amplitude parameters were calculated to characterize the spatial distribution of muscle activity. LBP group showed a less ES activity than HC (lower root mean square across the grid and of the activation region) and an involvement of the same muscular area across the task (lower coefficient of variation of the center of gravity of muscle activity). The results indicate the usefulness of HDsEMG parameters to classify risk levels for both HC and LBP groups and to determine differences between them. The findings suggest that the use of HDsEMG could expand the capabilities of existing instrumental-based tools for biomechanical risk classification during lifting activities.

Original languageEnglish
Article number102839
Number of pages9
JournalJournal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
Volume73
Early online date4 Nov 2023
DOIs
Publication statusPublished - Dec 2023

Bibliographical note

Funding:
The research presented in this article was carried out as part of the program BRIC 2016-ID10 funded by INAIL and as part of the SOPHIA project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 871237.

Copyright:
© 2023 Elsevier Ltd. All rights reserved.

Keywords

  • Humans
  • Low Back Pain
  • Electromyography/methods
  • Muscle, Skeletal/physiology
  • Muscle Fatigue
  • Paraspinal Muscles

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