Developed in-home monitoring models that uses data from unintrusive sensors to monitor the movement patterns of older adults, and to detect behavioural changes that may indicate potential health issues (urinary anomalies and cognitive deterioration).
Campus location
AustraliaPrincipal supervisor
Ingrid ZukermanAdditional supervisor 1
Mahsa SalehiAdditional supervisor 2
Mor VeredYear of Award
2025Department, School or Centre
Data Science & Artificial IntelligenceCourse
Doctor of PhilosophyDegree Type
DOCTORATEFaculty
Faculty of Information TechnologyRights Statement
The author retains copyright of this thesis. It must only be used for personal non-commercial research, education and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission. For further terms use the In Copyright link under the License field.
