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Article

The assistance of BAZAR robot promotes improved upper limb motor coordination in workers performing an actual use-case manual material handling

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Pages 1950-1967 | Received 19 Sep 2022, Accepted 14 Jan 2023, Published online: 26 Jan 2023
 

Abstract

This study aims at evaluating upper limb muscle coordination and activation in workers performing an actual use-case manual material handling (MMH). The study relies on the comparison of the workers’ muscular activity while they perform the task, with and without the help of a dual-arm cobot (BAZAR). Eleven participants performed the task and the flexors and extensors muscles of the shoulder, elbow, wrist, and trunk joints were recorded using bipolar electromyography. The results showed that, when the particular MMH was carried out with BAZAR, both upper limb and trunk muscular co-activation and activation were decreased. Therefore, technologies that enable human-robot collaboration (HRC), which share a workspace with employees, relieve employees of external loads and enhance the effectiveness and calibre of task completion. Additionally, these technologies improve the worker’s coordination, lessen the physical effort required to interact with the robot, and have a favourable impact on his or her physiological motor strategy.

Practitioner summary: Upper limb and trunk muscle co-activation and activation is reduced when a specific manual material handling was performed with a cobot than without it. By improving coordination, reducing physical effort, and changing motor strategy, cobots could be proposed as an ergonomic intervention to lower workers’ biomechanical risk in industry.

Acknowledgments

We are extremely grateful to Freek Tonis and Pim Siahaya from HANKAMP for their help with the experimental procedure.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are openly available in https://gite.lirmm.fr/humar/research-projects/sophia_dataset_example.

Additional information

Funding

The research presented in this article was carried out 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.

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