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 ....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.Read moreRead less
New strategies for characterising and monitoring protein-surface interactions: application to a biosensor for diabetic’s blood glucose regime effectiveness. This project aims to develop an antibody based biosensor for the detection of glycosylated haemoglobin (HbA1c) which serves as a marker of the effectiveness of a diabetic’s blood glucose treatment regime. Monitoring HbA1c is important as many of the long term health effects of diabetes are a consequence of high blood glucose levels. The si ....New strategies for characterising and monitoring protein-surface interactions: application to a biosensor for diabetic’s blood glucose regime effectiveness. This project aims to develop an antibody based biosensor for the detection of glycosylated haemoglobin (HbA1c) which serves as a marker of the effectiveness of a diabetic’s blood glucose treatment regime. Monitoring HbA1c is important as many of the long term health effects of diabetes are a consequence of high blood glucose levels. The simple to use technology will be a general detection strategy for proteins and hence will be applicable for the detection of a wide range of diseases and biomarkers. The research will also benefit Australia by training the new generation of scientists for Australia's biomedical diagnostics industry.Read moreRead less
RNA-based analysis for prediction of islet death in diabetes. Death of insulin-producing cells is a common feature in diabetes. Presently, a blood glucose test remains the only blunt instrument to diagnose diabetes. The RNA-based analysis for prediction of islet death in diabetes (RAPID) study links with eight clinical trials to test this newly developed non-invasive assay for predicting diabetes. Early diagnosis will help to reduce diabetic complications in later life.