Research Grant
[Cite as https://purl.org/au-research/grants/arc/DP150100116]Researchers: Dr Dylan Cliff (Chief Investigator) , Markus Hagenbuchner (Chief Investigator) , Professor Stewart Trost (Chief Investigator)
Brief description Modelling active play in preschool children using machine learning. This interdisciplinary project explores novel machine learning approaches to modelling physical activity data in preschool children. The approach taken is considered the future of physical activity assessment and is expected to substantially enhance the measurement of physical activity and the evidence base that informs strategies to improve population health through physical activity promotion. The project aims to transform the understanding of young children's physical activity behaviour, and is expected to have important implications for the design of accurate and effective technology-based physical activity monitoring and intervention applications that could be delivered through the e-health initiative in Australia.
Funding Amount $286,424
Funding Scheme Discovery Projects
- PURL : https://purl.org/au-research/grants/arc/DP150100116
- ARC : DP150100116