Modelling active play in preschool children using machine learning (ARC Discovery Project administered by the University of Wollongong) (2015)
Source: https://about.uq.edu.au/experts/project/23928 Parent: https://about.uq.edu.au/experts/934
Abstract
This interdisciplinary project explores novel machine learning approaches to modelling physical activity monitor 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 will transform our understanding of young children¿s physical activity behaviour, and will 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.
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Experts
Professor Stewart Trost
Professorial Research Fellow : School of Human Movement and Nutrition Sciences : Faculty of Health, Medicine and Behavioural Sciences
Affiliate of Health and Wellbeing Centre for Research Innovation : Health and Wellbeing Centre for Research Innovation : Faculty of Health, Medicine and Behavioural Sciences
Affiliate of Queensland Cerebral Palsy Rehabilitation and Research Centre : Queensland Cerebral Palsy Rehabilitation and Research Centre : Faculty of Health, Medicine and Behavioural Sciences
Affiliate of Child Health Research Centre : Child Health Research Centre : Faculty of Health, Medicine and Behavioural Sciences
Grant type : University of Wollongong
Funded by : University of Wollongong