Real-time Estimation of the Strength Capacity of the Upper Limb for Physical Human-Robot Collaboration

Aldini, S; Lai, Y; Carmichael, MG; Paul, G; Liu, D

Real-time Estimation of the Strength Capacity of the Upper Limb for Physical Human-Robot Collaboration

Aldini, S

Lai, Y

Carmichael, MG Paul, G

Liu, D

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021, 2021, pp. 4533-4536
Issue Date:: 2021-12-09

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Field	Value	Language
dc.contributor.author	Aldini, S https://orcid.org/0000-0001-5411-3850
dc.contributor.author	Lai, Y https://orcid.org/0000-0002-9381-5836
dc.contributor.author	Carmichael, MG
dc.contributor.author	Paul, G https://orcid.org/0000-0002-3478-0020
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582
dc.date	2021-11-01
dc.date.accessioned	2022-06-18T00:01:42Z
dc.date.available	2022-06-18T00:01:42Z
dc.date.issued	2021-12-09
dc.identifier.citation	2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021, 2021, pp. 4533-4536
dc.identifier.isbn	9781728111797
dc.identifier.issn	2375-7477
dc.identifier.issn	2694-0604
dc.identifier.uri	http://hdl.handle.net/10453/158233
dc.description.abstract	In physical Human-Robot Collaboration (pHRC), having an estimate of the operator’s strength capacity can help implement control strategies. Currently, the trend is to integrate devices that can measure physiological signals. This is not always a viable option, especially for highly dynamic tasks. For pHRC tasks, the physical interaction point usually occurs at the operator’s hand. Therefore, a musculo-skeletal model was used to have a real-time estimation of the strength capacity of the operator’s upper limb. First, the model has been simplified to reduce the complexity of the problem. The model was used to obtain offline estimations of the strength capacity, that were then curve-fitted to enable real-time estimation. An experiment was carried out to compare the results of the approximated model with human data. Results suggest that this method for estimating the strength capacity of the upper limb is a viable solution for real-time applications.
dc.format	Print
dc.language	en
dc.publisher	IEEE
dc.relation	http://purl.org/au-research/grants/arc/LP140100950
dc.relation.ispartof	2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
dc.relation.ispartof	2021 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
dc.relation.ispartofseries	IEEE Engineering in Medicine and Biology Society Conference Proceedings
dc.relation.isbasedon	10.1109/embc46164.2021.9630230
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject.mesh	Hand
dc.subject.mesh	Humans
dc.subject.mesh	Musculoskeletal System
dc.subject.mesh	Robotics
dc.subject.mesh	Upper Extremity
dc.subject.mesh	Upper Extremity
dc.subject.mesh	Hand
dc.subject.mesh	Musculoskeletal System
dc.subject.mesh	Humans
dc.subject.mesh	Robotics
dc.title	Real-time Estimation of the Strength Capacity of the Upper Limb for Physical Human-Robot Collaboration
dc.type	Conference Proceeding
utslib.citation.volume	2021
utslib.location.activity	Mexico
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2023-12-09T00:00:00+1000Z
dc.date.updated	2022-06-18T00:01:41Z
pubs.finish-date	2021-11-05
pubs.publication-status	Published
pubs.start-date	2021-11-01
pubs.volume	2021

Abstract:

In physical Human-Robot Collaboration (pHRC), having an estimate of the operator’s strength capacity can help implement control strategies. Currently, the trend is to integrate devices that can measure physiological signals. This is not always a viable option, especially for highly dynamic tasks. For pHRC tasks, the physical interaction point usually occurs at the operator’s hand. Therefore, a musculo-skeletal model was used to have a real-time estimation of the strength capacity of the operator’s upper limb. First, the model has been simplified to reduce the complexity of the problem. The model was used to obtain offline estimations of the strength capacity, that were then curve-fitted to enable real-time estimation. An experiment was carried out to compare the results of the approximated model with human data. Results suggest that this method for estimating the strength capacity of the upper limb is a viable solution for real-time applications.

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http://hdl.handle.net/10453/158233