Assessment of a passive exoskeleton system on spinal biomechanics and subjective responses during manual repetitive handling tasks among construction workers

Abstract

An exoskeleton system can be an effective ergonomic intervention for mitigating the risks of developing work-related musculoskeletal disorders, yet little attention is given to the effects of its application on physical risk factors and subjective responses. Therefore, the objective of this study was to examine the effects of a passive exoskeleton system on spinal biomechanics and subjective responses during manual repetitive handling tasks among construction workers. Muscle activity of the Thoracic Erector Spinae (TES), Lumbar Erector Spinae (LES) at L3 vertebrae level, Rectus Abdominis (RA), and External Oblique (EO) during the repetitive handling tasks were measured by surface electromyography (sEMG). Additionally, the Borg categorical rating scale (Borg CR 10), local perceived pressure (LPP), and system usability scale (SUS) were used to measure the ratings of perceived discomfort, perceived musculoskeletal pressure, and system usability, respectively. Our results found that: (1) the use of the passive exoskeleton system significantly reduced LES muscle activity (11–33% MVC), with a greater reduction in LES muscle activity (32.71% MVC) for the heaviest lifting load; (2) the use of the passive exoskeleton system significantly reduced perceived discomfort scores (42.40%) of the lower back for the heaviest lifting load; (3) increased lifting load significantly increased LPP scores of the shoulder, lower back, and leg body parts; and (4) majority of the participants rated the passive exoskeleton system as having acceptable usability. The findings of these results indicate that the developed passive exoskeleton system could reduce the internal muscle force, extensor moments, and spinal forces in the lumbar region.

Publication DOI: https://doi.org/10.1016/j.ssci.2021.105382
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Engineering Systems and Supply Chain Management
Additional Information: © 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ Funding: The authors acknowledged these funding grants: 1. General Research Fund (GRF) Grant (BRE/PolyU 152047/19E) entitled “In search of a suitable tool for proactive physical fatigue assessment: an invasive to non-invasive approach”; 2. General Research Fund (GRF) Grant (BRE/PolyU 15210720) entitled “The development and validation of a non-invasive tool to monitor mental and physical stress in construction workers” and 3. Aston Institute for Urban Technology and the Environment (ASTUTE), Seedcorn Grants Proposal entitled “Wearable insole sensor data and a deep learning network-based recognition for musculoskeletal disorders prevention in construction”.
Uncontrolled Keywords: Construction workers,Ergonomic intervention,Exoskeleton,Manual repetitive handling tasks,Muscle activity
Full Text Link:
Related URLs: https://linking ... 925753521002265 (Publisher URL)
PURE Output Type: Article
Published Date: 2021-10-01
Published Online Date: 2021-06-18
Accepted Date: 2021-06-09
Authors: Antwi-afari, Maxwell Fordjour (ORCID Profile 0000-0002-6812-7839)
Li, Heng
Anwer, Shahnawaz
Li, Dawei
Yu, Yi
Mi, Hao-yang
Wuni, Ibrahim Yahaya

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Version: Accepted Version

Access Restriction: Restricted to Repository staff only until 18 December 2022.

License: Creative Commons Attribution Non-commercial No Derivatives


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