Automated Insulin Delivery (AID)
DeviceThe AID control algorithm, that will be used during the study employs a model-based predictive control algorithm to forecast future glucose levels. This predictive model accounts for the impact of delivered insulin, user-entered carbohydrates, and incorporates two short-term adaptations: "glucose momentum" and "retrospective correction." These features work to optimize glucose management with precision. The impact of carbohydrates is calculated based on the user-defined insulin-to-carbohydrate ratio and insulin sensitivity factor (ISF), while the insulin effect is governed by the ISF itself. The system then dynamically adjusts insulin delivery, aiming to bring glucose levels in line with the midpoint of the user's personalized glucose target range. Loop fine-tunes insulin delivery by increasing or decreasing the basal insulin rate, as needed, each time a new CGM value is received.