Towards Safe and Robust Closed-Loop Artificial Pancreas Using Improved PID-Based Control Strategies

Abstract

Artificial pancreas enhances the life experience for diabetic patients by allowing them to live normally with their glucose levels controlled automatically with minimal or no intervention. For closed-loop glucose controllers to be approved for clinical practice, they have to prove safety under all potential scenarios. One of the biggest challenges of closed-loop glucose control is to handle the distortion caused by meal intake. This challenge becomes more problematic when taking into account the imperfections and limitations of glucose sensors. In this article, we propose new Proportional-Integral-Derivative (PID)-based control strategies for robust glucose control under varying meal conditions. The proposed approaches aim at counteracting the challenges imposed by the large delays incurred in glucose sensing and insulin action. Statistical model checking was utilized to analyze the performance figures and safety properties as compared with existing closed-loop techniques. The results have shown that one of the proposed approaches provide substantial enhancements towards safe and robust glucose control especially under sensor noise. Where, under a typical relative meal size between 75 and 125 (g/100Kg), the proposed approach can satisfy hypoglycemia safety property for 90% of the patients compared to lower than 50% of the patients for the other investigated techniques. These enhancements can be achieved without additional personalized tuning beyond the standard PID control.