PhD Position: Automated Eating Activity Tracking System for Anorexia Nervosa Using AI and Wearable Sensors

This fully funded PhD position at KU Leuven focuses on creating an AI-powered wearable sensor system to track eating behavior in individuals with anorexia nervosa. The project combines expertise from the eMedia Research Lab (specializing in AI, machine learning, and digital health) and the Mind-Body Research Group (clinical neuroscience and eating disorders). The PhD researcher will design data acquisition protocols, develop machine learning pipelines for wearable sensor data, and create interpretable digital biomarkers to quantify eating patterns. The work involves close collaboration with clinicians, psychologists, and engineers to translate AI methods into real-world healthcare applications. The interdisciplinary environment offers opportunities for innovation in digital biomarkers and continuous monitoring for eating disorders.

• Design and optimize wearable-based data acquisition protocols for monitoring eating behavior using inertial measurement unit (IMU) sensors.
• Develop robust signal processing and machine learning pipelines to extract eating-related behavioral patterns from sensor data.
• Create interpretable digital biomarkers that quantify key micro-structural properties of eating behavior, such as eating speed, rigidity, and variability.
• Investigate relationships between wearable-derived biomarkers and clinical outcomes, including illness severity and treatment progress.
• Collaborate closely with clinicians, psychologists, and researchers to translate AI-based methods into real-world healthcare applications.
• Disseminate research findings through peer-reviewed publications, conferences, and outreach activities.