AI-enabled and inclusive behavioural interventions for youth NCD prevention

Our centre contributes an integrated capability set to design, implement and validate behavioural interventions for the primary prevention of non-communicable diseases in young people, with particular attention to inclusion, equity and real-life deployment.

The Big Data Science unit can lead intersectional analyses of behavioural patterns across gender, age and socio-economic dimensions, integrating real-world data with complementary open datasets to identify early risk profiles linked to physical inactivity, diet and sleep behaviours.

The Robotics unit contributes an embodied and explainable AI layer that translates school- and community-level health objectives into structured, safe and adaptive task flows. These enable guided routines for physical activity, nutrition and sleep, ensuring transparency, robustness and compatibility with educational and community settings.

Through the Functional Textiles and Printed Embedded Devices unit, we develop soft, wearable and unobtrusive sensing systems for self-monitoring, building on experience in textile-based and embedded sensors suited for young populations and continuous use.

The Nutrition and Health and Omics Science units can design and execute studies in young populations to validate behavioural and biological outcomes, including markers related to metabolic health and sleep regulation. This includes generation and analysis of biological data arising from intervention and monitoring studies.

Together, these capabilities connect behavioural science, digital technologies and biological evidence into scalable, inclusive and evidence-based prevention strategies aligned with EU priorities on youth health and long-term NCD risk reduction.