Improving shiftworkers sleep and physical activity using machine learning. This project aims to develop a smartphone-enabled digital assistant to optimise sleep and physical activity for Australians w

Description

Improving shiftworkers sleep and physical activity using machine learning. This project aims to develop a smartphone-enabled digital assistant to optimise sleep and physical activity for Australians working non-standard hours, resulting in critical benefits for workplace productivity and safety. By harnessing advanced machine learning techniques and integrating wearable technology, this project aims to cater specifically to the unpredictable and variable hours of shiftworkers, on-call workers, and gig workers - something current tools do not. The expected outcome is a scalable digital assistant that provides personalised sleep and physical activity advice based on individual work patterns. This project is designed to provide new knowledge on personalised behavioural interventions using machine learning.. Scheme: Discovery Early Career Researcher Award. Field: 5203 - Clinical and Health Psychology. Lead: A/Prof Grace Vincent