Abstract: A method, system, and computer-readable medium are provided for an Automated Insulin Delivery (AID) system in which Model Predictive Control (MPC) thereof implements weighting of glucose target error relative to corresponding predicted blood glucose (BG) levels according to insulin on board (IOB). Accordingly, basal insulin infusion and available additional bolusing each in connection with glycemic disturbances such as unannounced meals can be proximally administered to maintain time in range (TIR) without incurring insulin stacking.

Abstract: A method, system, and computer-readable medium are provided for a dual mode Closed-Loop Control (CLC) system integrating each of (i) an adaptive, personalized Model Predictive Control (MPC) control law that modulates the control strength of insulin infusion depending on recent past control actions, glucose measurements, and their derivative(s), (ii) an automatic Bolus Priming System (BPS) that commands additional insulin injections upon the detection of enabling metabolic conditions (e.g., an unannounced meal), and (iii) a hyperglycemia mitigation system (HMS) to avoid prevailing hyperglycemia.

Abstract: Embodiments relate to systems and methods for informing, determining, or controlling insulin dosage. The method involves generating plural disturbance profiles, each disturbance profile being a data representation based on historical patient data pertaining to a deviation from a threshold blood glucose level. The method involves receiving current patient data. The method involves applying a predictive model so that current patient data is compared to a disturbance profile and a probability analysis is used to assess the likelihood of a disturbance profile being an anticipated disturbance profile, the anticipated disturbance profile being a disturbance profile that is determined to match with the current patient data based on the probability analysis. The method involves determining an insulin dose amount based on the anticipated disturbance profile.

Abstract: Provided are a system and method for an artificial pancreas having multi-stage model predictive control to minimize and/or prevent occurrence of hypoglycemia associated with Type 1 diabetes. The control implements predictive modeling of a probability of glucose uptake associated with exercise based on at least one exercise profile for a subject with Type 1 diabetes. Based on the probability, the control implements an automatic adjustment of basal insulin infusion to counteract a risk of exercise-induced hypoglycemia in advance of the subject engaging in the exercise. The control implements adjustment of such infusion based on real-time signaling of exercise likely to induce hypoglycemia. The control implements adjustment of a meal-time bolus to account for delay in glucose uptake resulting from exercise engaged in by the subject. Consequently, the control acts to minimize and/or prevent hypoglycemia from occurring both during and immediately after exercise.