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dc.contributor.authorHendry, Danica
dc.contributor.supervisorAmity Campbellen_US
dc.contributor.supervisorLeon Strakeren_US
dc.contributor.supervisorPeter O'Sullivanen_US
dc.date.accessioned2022-05-09T08:13:11Z
dc.date.available2022-05-09T08:13:11Z
dc.date.issued2021en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11937/88432
dc.description.abstract

This thesis explored the relationship between dancers' movement quantity and quality with pain outcomes. Machine learning models applied to wearable sensor data that were capable of field-based, objective quantification of dancers' movement quantity and quality were developed. This system was used in a longitudinal, field-based study to explore the relationship of pre-professional, female dancers movement quantity and quality with pain and pain related disability.

en_US
dc.publisherCurtin Universityen_US
dc.titleAn Investigation of Pain Related Disability with Movement Quantity and Quality in Pre-Professional Dancersen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentSchool of Physiotherapy and Exercise Scienceen_US
curtin.accessStatusOpen accessen_US
curtin.facultyHealth Sciencesen_US
curtin.contributor.orcidHendry, Danica [0000-0001-8701-2212]en_US


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