1. Wearable Sensors and Real-World Mobility Monitoring Developing and validating algorithmic pipelines to extract meaningful movement data (such as walking and Sit-to-Stand transfers) from unobtrusive wearable sensors during activities of daily living.
2. Digital Biomarkers for Aging Identifying and standardizing robust digital mobility outcomes (DMOs) to assess physical decline, sarcopenia, and functional capacity in older adults across large-scale multi-centric cohorts (e.g., Mobilise-D, InCHIANTI).
3. Fall Risk Assessment and Prevention Creating multi-domain, sensor-based assessments to continuously evaluate and stratify fall risk in community-dwelling older adults and specific clinical populations, moving beyond traditional supervised clinical tests.
4. Explainable Artificial Intelligence (XAI) in Healthcare Applying advanced, non-linear machine learning techniques to real-world mobility data to build transparent predictive models that aid clinicians in early diagnosis and personalized preventive care.
