Wearable Health: Data, AI, and Clinical Translation

3 credits · Graduate

This course provides an end-to-end introduction to wearable technologies for health, spanning physiological sensing, data collection and APIs, signal processing, artificial intelligence, machine learning, foundation models, clinical validation, and translation. Students will work with real-world wearable data and explore topics including digital biomarkers, multimodal and foundation models, data quality and missingness, study design, regulatory considerations, data privacy and security, and deployment. Sleep data and sleep disorders will serve as recurring clinical use cases throughout the course. The course combines lectures, hands-on data analysis, guest speakers from academia and industry, and a team-based final project.