IEEEEMBS-Boston Presents "Digital Twins for Diabetes: Modeling Glucose Regulation from Wearable Data"

Continuous glucose monitors, insulin pumps, and consumer wearables now produce uninterrupted streams of real-life physiological data, yet turning those streams into reliable physiological insight remains an open engineering problem. This talk follows a modeling program that moves from tightly controlled clinical studies into everyday outpatient conditions: oral glucose minimal models that estimate gastric retention, glucose rate of appearance, and insulin sensitivity from type 1 diabetes data collected in free living; nonlinear mixed effects models that quantify how dietary fat and protein reshape the postprandial glucose excursion; and mechanistic models of physical activity and glucose tolerance in type 2 diabetes built from CGM and smartwatch signals. In this webinar, Dr. Edoardo Faggionato traces a modeling program that moves from tightly controlled clinical studies into everyday outpatient conditions.