A Framework for Gamification of Human Joint Remote Rehabilitation, Incorporating Non-Invasive Sensors
dc.contributor.author | Khaksar, Siavash | |
dc.contributor.supervisor | Iain Murray | en_US |
dc.contributor.supervisor | Tele Tan | en_US |
dc.date.accessioned | 2024-03-25T03:45:05Z | |
dc.date.available | 2024-03-25T03:45:05Z | |
dc.date.issued | 2023 | en_US |
dc.identifier.uri | http://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.publisher | Curtin University | en_US |
dc.title | A Framework for Gamification of Human Joint Remote Rehabilitation, Incorporating Non-Invasive Sensors | en_US |
dc.type | Thesis | en_US |
dcterms.educationLevel | PhD | en_US |
curtin.department | School of Electrical Engineering, Computing and Mathematical Sciences | en_US |
curtin.accessStatus | Open access | en_US |
curtin.faculty | Science and Engineering | en_US |
curtin.contributor.orcid | Khaksar, Siavash [0000-0002-1944-1418] | en_US |