Validation of endurance model for manual tasks*

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dc.contributor.authorO’Sullivan, Patriciaen
dc.contributor.authorMenolotto, Matteoen
dc.contributor.authorO’Flynn, Brendanen
dc.contributor.authorKomaris, Dimitrios-Sokratisen
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2024-02-09T08:24:24Z
dc.date.available2024-02-09T08:24:24Z
dc.date.issued2023-12-11en
dc.description.abstractPhysical fatigue in the workplace can lead to work-related musculoskeletal disorders (WMSDs), especially in occupations that require repetitive, mid-air movements, such as manufacturing and assembly tasks in industry settings. The current paper endeavors to validate an existing torque-based fatigue prediction model for lifting tasks. The model uses anthropometrics and the maximum torque of the individual to predict the time to fatigue. Twelve participants took part in the study which measured body composition parameters and the maximum force produced by the shoulder joint in flexion, followed by three lifting tasks for the shoulder in flexion, including isometric and dynamic tasks with one and two hands. Inertial measurements units (IMUs) were worn by participants to determine the torque at each instant to calculate the endurance time and CE, while a self-subjective questionnaire was utilized to assess physical exertion, the Borg Rate of Perceived Exertion (RPE) scale. The model was effective for static and two-handed tasks and produced errors in the range of [28.62 49.21] for the last task completed, indicating the previous workloads affect the endurance time, even though the individual perceives they are fully rested. The model was not effective for the one-handed dynamic task and differences were observed between males and females, which will be the focus of future work.An individualized, torque-based fatigue prediction model, such as the model presented, can be used to design worker-specific target levels and workloads, take inter and intra individual differences into account, and put fatigue mitigating interventions into place before fatigue occurs; resulting in potentially preventing WMSDs, aiding in worker wellbeing and benefitting the quality and efficiency of the work output.Clinical Relevance— This research provides the basis for an individualized, torque-based approach to the prediction of fatigue at the shoulder joint which can be used to assign worker tasks and rest breaks, design worker specific targets and reduce the prevalence of work-related musculoskeletal disorders in occupational settings.en
dc.description.sponsorshipScience Foundation Ireland (12/RC/2289-P2 INSIGHT)en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationO’Sullivan, P., Menolotto, M., O’Flynn, B. and Komaris, D.-S. (2023) 'Validation of endurance model for manual tasks*', 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Sydney, Australia, 24-27 July, pp. 1-5, doi: https://doi.org/10.1109/EMBC40787.2023.10341139en
dc.identifier.doihttps://doi.org/10.1109/EMBC40787.2023.10341139en
dc.identifier.eissn2694-0604en
dc.identifier.endpage5en
dc.identifier.isbn979-8-3503-2447-1en
dc.identifier.isbn979-8-3503-2448-8en
dc.identifier.issn2375-7477en
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/15537
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.ispartof2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Sydney, Australia, 24-27 Julyen
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres Programme::Phase 1/16/RC/3918/IE/Confirm Centre for Smart Manufacturing/en
dc.rights© 2023, the Authors. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see https://creativecommons.org/licenses/by/3.0/en
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/en
dc.subjectMusculoskeletal systemen
dc.subjectTorqueen
dc.subjectMeasurement unitsen
dc.subjectShoulderen
dc.subjectPredictive modelsen
dc.subjectFatigueen
dc.subjectParticle measurementsen
dc.titleValidation of endurance model for manual tasks*en
dc.typeConference itemen
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