The impact of glucose sensing dynamics on the closed-loop artificial pancreas

Abstract

A closed-loop artificial pancreas (AP) to provide automated treatment for people with type 1 diabetes mellitus has the potential to improve patient health outcomes; however, the system's success hinges on its ability to quickly detect and react to changing blood glucose concentrations (BG). In this study, the impact of measurement lag on AP robust stability, performance, and time-domain disturbance rejection was investigated and compared to the case of an ideal BG sensor. The analysis was performed for an AP using either intraperitoneal (IP) or subcutaneous (SC) insulin delivery routes. Decreasing the sensor lag resulted in a higher tolerance for model uncertainty for robust stability and performance. In the case of a 20 min sensor lag, the time spent in hyperglycemia after a meal disturbance was 59±19 min and 120 ±22 min for IP and SC insulin, respectively. Switching the sensor to the ideal case decreased the time spent in hyperglycemia by 21±8 min for IP insulin and by 13±3 min for SC insulin. Since the SC system already contains large actuation delays, a faster sensor is not as important to improved performance as it is in the IP case. Significant gains in AP performance can be achieved with the use of IP insulin, but these improvements will not be fully realized unless faster glucose sensing is implemented as well.