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Application of Inertial Measurement Units and Machine Learning Classification in Cerebral Palsy: Randomized Controlled Trial

dc.contributor.authorKhaksar, Siavash
dc.contributor.authorPan, Huizhu
dc.contributor.authorBorazjani, Bita
dc.contributor.authorMurray, Iain
dc.contributor.authorAgrawal, Himanshu
dc.contributor.authorLiu, W
dc.contributor.authorElliott, Catherine
dc.contributor.authorImms, C
dc.contributor.authorCampbell, Amity
dc.contributor.authorWalmsley, Corrin
dc.date.accessioned2021-10-20T17:14:41Z
dc.date.available2021-10-20T17:14:41Z
dc.date.issued2021
dc.identifier.citationKhaksar, S. Khaksar S, Pan H, Borazjani B, Murray I, Agrawal H, Liu W, Elliott C, Imms C, Campbell A, Walmsley C. 2021. Application of Inertial Measurement Units and Machine Learning Classification in Cerebral Palsy: Randomized Controlled Trial. JMIR Rehabilitation and Assistive Technologies. 8 (4): Article No. e29769
dc.identifier.urihttp://hdl.handle.net/20.500.11937/86125
dc.identifier.doi10.2196/29769
dc.description.abstract

This paper presents collaborative research between the School of Electrical Engineering, Computing and Mathematical Sciences at Curtin University and a team of clinicians in a multicenter randomized controlled trial involving children with CP. This study aims to develop a digital solution for mass data collection using inertial measurement units (IMUs) and the application of machine learning (ML) to classify the movement features associated with CP to determine the effectiveness of therapy. The results were calculated without the need to measure Euler, quaternion, and joint measurement calculation, reducing the time required to classify the data.
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/nhmrc/1057997
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleApplication of Inertial Measurement Units and Machine Learning Classification in Cerebral Palsy: Randomized Controlled Trial
dc.typeJournal Article
dcterms.source.titleJMIR Rehabilitation and Assistive Technologies
dc.date.updated2021-10-20T17:14:40Z
curtin.departmentSchool of Elec Eng, Comp and Math Sci (EECMS)
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidKhaksar, Siavash [0000-0002-1944-1418]


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