A Closed-Loop Artificial Pancreas Using Model Predictive Control and a Sliding Meal Size Estimator

Abstract

The objective of this article is to present a comprehensive strategy for a closed-loop artificial pancreas. A meal detection and meal size estimation algorithm is developed for situations in which the subject forgets to provide a meal insulin bolus. A pharmacodynamic model of insulin action is used to provide insulin-on-board constraints to explicitly include the future effect of past and currently delivered insulin boluses. In addition, a supervisory pump shut-off feature is presented to avoid hypoglycemia. All of these components are used in conjunction with a feedback control algorithm using model predictive control (MPC). A model for MPC is developed based on a study of 20 subjects and is tested in a hypothetical clinical trial of 100 adolescent and 100 adult subjects using a Food and Drug Administration-approved diabetic subject simulator. In addition, a performance comparison of previously and newly proposed meal size estimation algorithms using 200 in silico subjects is presented. Using the new meal size estimation algorithm, the integrated artificial pancreas system yielded a daily mean glucose of 138 and 132 mg/dl for adolescents and adults, respectively, which is a substantial improvement over the MPC-only case, which yielded 159 and 145 mg/dl.

Digital mockups for the testing of a medical ventilator

“…Lee [7] described the need for the accurate modeling of patients to deliver higherconfidence devices. Arney [1] used a patient model consisting of drug absorption levels and patient vitals to test a closed-loop system of heterogeneous medical devices which includes a PCA pump and pulse oximeter.…”

Smith Predictor Sliding Mode Closed-loop Glucose Controller in Type 1 Diabetes

“…Meal announcement provides better results, however, it is not uncommon that patients forget to activate the meal bolus. Therefore, meal detection algorithms are developed to improve the control outcomes without requiring patient intervention (Lee et al [2009]). …”

MEDS: Mockup Electronic Data Sheets for automated testing of cyber-physical systems using digital mockups

“…Arney [1] uses a patient model consisting of drug absorption levels and patient vitals to test a closed-loop system of medical devices including a PCA pump and pulse oximeter. Lee presents a closed-loop artificial pancreas design [8], which is validated through the use of a human diabetic subject simulator [7]. Sirowy [14] introduced a technique for bypassing transducers to enable direct interaction between environmental models and cyber devices.…”