Exploring the Application of Wearable Movement Sensors in People with Knee Osteoarthritis
dc.contributor.author | Tan, Jay-Shian | |
dc.contributor.supervisor | Peter Kent | en_US |
dc.contributor.supervisor | Amity Campbell | en_US |
dc.date.accessioned | 2023-05-09T04:53:24Z | |
dc.date.available | 2023-05-09T04:53:24Z | |
dc.date.issued | 2022 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/91981 | |
dc.description.abstract |
People with knee osteoarthritis have difficulty with functional activities, such as walking or get into/out of a chair. This thesis explored the clinical relevance of biomechanics and how wearable sensor technology may be used to assess how people move when their clinician is unable to directly observe them, such as at home or work. The findings of this thesis suggest that artificial intelligence can be used to process data from sensors to provide clinically important information about how people perform troublesome activities. | en_US |
dc.publisher | Curtin University | en_US |
dc.title | Exploring the Application of Wearable Movement Sensors in People with Knee Osteoarthritis | en_US |
dc.type | Thesis | en_US |
dcterms.educationLevel | PhD | en_US |
curtin.department | Curtin School of Allied Health | en_US |
curtin.accessStatus | Open access | en_US |
curtin.faculty | Health Sciences | en_US |
curtin.contributor.orcid | Tan, Jay-Shian [0000-0002-9728-3128] | en_US |