Approved Research

Mining Physical Activity and Nutrition Data for Guiding Healthier Behaviour

Lay summary

This research project aims to merge data mining with health science to understand and enhance human health by discovering and analysing physical activity and nutrition patterns. Recognizing that sedentary lifestyles and poor diets are primary contributors to obesity and non-communicable diseases, this study seeks to uncover the complex relationship between these factors. By harnessing machine learning and deep learning, the project will extract meaningful patterns from accelerometer data and digital dietary records to develop a dashboard. This dashboard will provide personalized recommendations and pathways to healthier behavior for individuals and valuable insights for health experts. The anticipated outcome is a set of predictive features, data structuring methods, and behavior clusters that will contribute to the fields of Data Mining, Machine Learning, and Human-Computer Interaction (HCI), with significant implications for public health.