Skip to main content

ORIGINAL RESEARCH article

Front. Bioeng. Biotechnol.
Sec. Biomechanics
Volume 13 - 2025 | doi: 10.3389/fbioe.2025.1486931
This article is part of the Research Topic Application of Biomechanics in Diagnosis & Therapy of Skeletal System Diseases View all 4 articles

Assessing low-back loading during lifting using personalized electromyography-driven trunk models and NIOSH-based risk levels

Provisionally accepted
  • 1 Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands, Enschede, Netherlands
  • 2 National Institute for Insurance against Accidents at Work (INAIL), Rome, Italy

The final, formatted version of the article will be published soon.

    Workplace injury risk due to physically demanding tasks (e.g., repeated lifting) is currently assessed using ergonomic guidelines. The Revised NIOSH Lifting Equation (RNLE) is a commonly used approach that assesses risk of low-back loading during different lifting tasks. Advances in musculoskeletal models have enabled the estimation of physiologically valid person-specific musculoskeletal models (pEMS) driven by surface electromyography and joint angle information. These models offer realistic estimates of objective parameters such as moments and compressive and shear loads at the lumbosacral joint. In this study, we applied both techniques (RNLE and pEMS) to assess risk and low-back loading in seven healthy participants performing lifting tasks at different risk levels. We found that the pEMS estimated objective parameters of low-back loading in line with the different risk levels proposed by RNLE. However, the low-back compressive and shear loads were higher than the limits proposed by the RNLE. Moreover, we show that the lumbosacral compressive loads can be a better parameter to demarcate risk levels. We recommend performing this assessment on a larger and diverse population for evaluation of personalized risk levels across lifting tasks in the industry. These approaches can be implemented with wearable sensorized garments to monitor personalized musculoskeletal health unobtrusively in the workplace providing us a better insight into possibility of individual risk.

    Keywords: Workplace musculoskeletal disorder, NIOSH, musculoskeletal modelling, Lifting, Electromyography

    Received: 27 Aug 2024; Accepted: 13 Jan 2025.

    Copyright: © 2025 Mohamed Refai, VARRECCHIA, Chini, Ranavolo and Sartori. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Mohamed Irfan Mohamed Refai, Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands, Enschede, Netherlands
    TIWANA VARRECCHIA, National Institute for Insurance against Accidents at Work (INAIL), Rome, Italy

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.