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dc.contributor.authorKhaksar, Siavash
dc.contributor.supervisorIain Murrayen_US
dc.contributor.supervisorTele Tanen_US
dc.date.accessioned2024-03-25T03:45:05Z
dc.date.available2024-03-25T03:45:05Z
dc.date.issued2023en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11937/94583
dc.description.abstract

Patients who have suffered soft tissue injuries or undergone surgery often experience reduced muscle strength, flexibility, and pain in the affected area, which can interfere with daily activities. Rehabilitation exercises are crucial in reducing symptoms and returning patients to normal activities. This research presents a framework for human joint rehabilitation that enables clinicians to set engaging gamified rehabilitation tasks for their patients utilising non-invasive sensors and machine learning algorithms.

en_US
dc.publisherCurtin Universityen_US
dc.titleA Framework for Gamification of Human Joint Remote Rehabilitation, Incorporating Non-Invasive Sensorsen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Sciencesen_US
curtin.accessStatusOpen accessen_US
curtin.facultyScience and Engineeringen_US
curtin.contributor.orcidKhaksar, Siavash [0000-0002-1944-1418]en_US


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