The Effect of Insulin Feedback on Closed Loop Glucose Control

Abstract

Insulin feedback can be implemented using a model estimate of concentration. Proportional integral derivative control with insulin feedback can achieve a desired breakfast response but still requires supplemental carbohydrate to be delivered in some instances. Studies assessing more optimal control configurations and safeguards need to be conducted.

Algorithms for a Closed-Loop Artificial Pancreas: The Case for Proportional-Integral-Derivative Control

“…Nonetheless, the nighttime results were not better than the nighttime results obtained with the initial PID controller modified with insulin feedback (PID IFB ). 4 The IQR of glucose values was higher ( Figure 3A) as was the reported incidence of hypoglycemia (7 events in 27 nights with MD-Logic versus 0 events in 9 nights of control with PID IFB , 4 or 6 events in 35 nights if the first three PID studies [2][3][4] shown in Figure 1 are combined). While the sCTR algorithm 24 had the lowest incidence of nighttime hypoglycemia (Figure 3C), the rate was achieved at the expense of having the highest nighttime glucose IQR ( Figure 3B).…”

“…4,5,6 The first report of PID IFB used only a small fixed bolus (2 U for all meals; Figure 3C). 4 This was later reduced to an even smaller bolus related to the subject's total daily dose of insulin (0.5, 1.0, and 1.5 U in subjects using <15, 15-30, and >30 U) 5 and then eliminated altogether in a study in children less than seven years old. 6 The study in children less than seven years old argued specifically that the bolus should not be given in children for safety reasons, as children may not always consume the anticipated carbohydrates.…”

“…This article will focus on the PID algorithms I have developed with my colleagues. [2][3][4][5][6][7][8] This version did not originate as a "PID" algorithm per se, 9 but rather as a model of β-cell insulin secretion, 10,11 referred to as "physiologic insulin delivery." It was, however, first implemented 2 using only the proportional, integral, and derivative terms needed to fit the β-cell response to a hyperglycemic clamp.…”

Recent Trends in Blood Glucose Control Studies

“…Some research groups [26,[30][31][32] have developed feedback blood glucose control systems combining CSII and continuous glucose monitoring (CGM) that adjust subcutaneous insulin infusion rates based on blood glucose measurements obtained from a micro needle implanted subcutaneously. Most of the control methods utilized in these systems are model predictive control (MPC) and proportional, integral and differential (PID) control.…”

“…Kovatchev et al [30] applied a system (Figure 2a) to T1D patients that adjusts insulin infusion rate using MPC based on blood glucose measured by CGM, and showed that it can reduce the frequency of hypoglycemia and maintain blood glucose levels longer within a desirable range during the night. Steil et al [31] constructed a modified PID control algorithm for T1D patients based on estimation of insulin concentration ( Figure 2b), and showed that it improves blood glucose profiles before breakfast, which usually tends to be hyperglycemic. Castle et al [32] developed a blood glucose control system (Figure 2c) using not only insulin but also glucagon, which is another important hormone for blood glucose regulation -especially to avoid hypoglycemia-and showed its effectiveness to reduce time of hypoglycemia, although its long-term effectiveness has not been examined.…”