A generic algorithm for computing optimal ergonomic postures during working in an industrial environment

The present study tries to decrease the risk of work-related musculoskeletal disorders for industry workers by proposing a generic algorithm that recommends an optimal ergonomic posture for accomplishing tasks in an industrial environment. In the case of a dangerous ergonomic pose, the optimization...

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Veröffentlicht in:International journal of industrial ergonomics 2021-07, Vol.84, p.103145, Article 103145
Hauptverfasser: Merikh-Nejadasl, Atieh, El Makrini, Ilias, Van De Perre, Greet, Verstraten, Tom, Vanderborght, Bram
Format: Artikel
Sprache:eng
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Zusammenfassung:The present study tries to decrease the risk of work-related musculoskeletal disorders for industry workers by proposing a generic algorithm that recommends an optimal ergonomic posture for accomplishing tasks in an industrial environment. In the case of a dangerous ergonomic pose, the optimization algorithm starts by heuristically changing it to a more ergonomic one. Each recommended posture's feasibility is tested with an inverse kinematic method that can predict the worker's behavior for accomplishing a task. This iterative optimization procedure continues until the optimal ergonomic pose for the worker is achieved. The algorithm's validity is tested in thirteen cases, people with different gender (50 percent male, 50 percent female) aged between 20 and 35, and different height and body morphologies. According to studies, there is a connection between musculoskeletal disorders and the wrong posture for accomplishing tasks in industries. We suggest an optimization algorithm that can indicate the worker the optimal ergonomic pose by considering task constraints in real-time. [Display omitted] •The postural optimization algorithm can show the correct way of doing a task for industrial workers.•Worker's ergonomic condition is assessed via motion capture devices, and the algorithm offers them a more ergonomic posture.•The validity of the algorithm tested on a dataset consisting of different people with different body morphologies.•The algorithm can be used in the control loop of exoskeletons or collaborative robots.
ISSN:0169-8141
1872-8219
DOI:10.1016/j.ergon.2021.103145