Machine Learning Derived Lifting Technique in People without Low Back Pain

Phan, TC; Pranata, A; Farragher, JB; Bryant, AL; Nguyen, HT; Chai, R

Machine Learning Derived Lifting Technique in People without Low Back Pain

Phan, TC Pranata, A Farragher, JB Bryant, AL Nguyen, HT Chai, R

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023, 2023, pp. 1-4
Issue Date:: 2023-12-11

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Field	Value	Language
dc.contributor.author	Phan, TC
dc.contributor.author	Pranata, A
dc.contributor.author	Farragher, JB
dc.contributor.author	Bryant, AL
dc.contributor.author	Nguyen, HT
dc.contributor.author	Chai, R https://orcid.org/0000-0002-1922-7024
dc.date	2023-07-24
dc.date.accessioned	2024-05-02T11:50:49Z
dc.date.available	2024-05-02T11:50:49Z
dc.date.issued	2023-12-11
dc.identifier.citation	2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023, 2023, pp. 1-4
dc.identifier.isbn	9798350324471
dc.identifier.issn	2375-7477
dc.identifier.issn	2694-0604
dc.identifier.uri	http://hdl.handle.net/10453/178534
dc.description.abstract	This paper presents a method for determining the number of lifting techniques used by healthy individuals through the analysis of kinematic data collected from 115 participants utilizing an motion capture system The technique utilizes a combination of feature extraction and Ward s method to analyse the range of motion in the sagittal plane of the knee hip and trunk The findings identified five unique lifting techniques in people without low back pain The multivariate analysis of variance statistical analysis reveals a significant difference in the range of motion in the trunk hip and knee between each cluster for healthy people F 12 646 125 720 p 0 0001 Clinical Relevance This information can assist healthcare professionals in choosing effective treatments and interventions for those with occupational lower back pain by focusing rehabilitation on specific body parts associated with problematic lifting techniques such as the trunk hip or knee which may lead to improved pain and disability outcomes exemplifying precision medicine
dc.format	Print
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
dc.relation.ispartof	2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
dc.relation.isbasedon	10.1109/embc40787.2023.10340260
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.mesh	Humans
dc.subject.mesh	Knee
dc.subject.mesh	Knee Joint
dc.subject.mesh	Lifting
dc.subject.mesh	Low Back Pain
dc.subject.mesh	Lower Extremity
dc.subject.mesh	Machine Learning
dc.subject.mesh	Lower Extremity
dc.subject.mesh	Knee
dc.subject.mesh	Knee Joint
dc.subject.mesh	Humans
dc.subject.mesh	Low Back Pain
dc.subject.mesh	Lifting
dc.subject.mesh	Machine Learning
dc.subject.mesh	Humans
dc.subject.mesh	Knee
dc.subject.mesh	Knee Joint
dc.subject.mesh	Lifting
dc.subject.mesh	Low Back Pain
dc.subject.mesh	Lower Extremity
dc.subject.mesh	Machine Learning
dc.title	Machine Learning Derived Lifting Technique in People without Low Back Pain
dc.type	Conference Proceeding
utslib.citation.volume	2023
utslib.location.activity	Sydney, Australia
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/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2024-05-02T11:50:47Z
pubs.finish-date	2023-07-27
pubs.publication-status	Published
pubs.start-date	2023-07-24
pubs.volume	2023

Abstract:

This paper presents a method for determining the number of lifting techniques used by healthy individuals through the analysis of kinematic data collected from 115 participants utilizing an motion capture system The technique utilizes a combination of feature extraction and Ward s method to analyse the range of motion in the sagittal plane of the knee hip and trunk The findings identified five unique lifting techniques in people without low back pain The multivariate analysis of variance statistical analysis reveals a significant difference in the range of motion in the trunk hip and knee between each cluster for healthy people F 12 646 125 720 p 0 0001 Clinical Relevance This information can assist healthcare professionals in choosing effective treatments and interventions for those with occupational lower back pain by focusing rehabilitation on specific body parts associated with problematic lifting techniques such as the trunk hip or knee which may lead to improved pain and disability outcomes exemplifying precision medicine

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http://hdl.handle.net/10453/178534