Closed-loop blood glucose control using dual subcutaneous infusion of insulin and glucagon based on switching PID controller

Glucose management is an important clinical task for diabetic patients, and intensive insulin therapy is widely considered a promising way for the glucose management. However, the intensive insulin therapy has one potential risk: hypoglycemia, but there is no antagonist to compensate hypoglycaemia in the intensive insulin therapy. Dual infusion of insulin and glucagon can overcome this shortcoming. In this paper, a switching control algorithm was proposed to design and optimize the insulin and glucagon infusion rates simultaneously, and this algorithm has been implemented in a virtual type 1 diabetic subject. The in silico results demonstrate that the proposed algorithm can reduce hypoglycaemia significantly.

[1]  F. Doyle,et al.  Model predictive control with learning‐type set‐point: Application to artificial pancreatic β‐cell , 2010 .

[2]  Guisheng Zhai,et al.  A Note on Multiple Lyapunov Functions and Stability Condition for Switched and Hybrid Systems , 2007, 2007 IEEE International Conference on Control Applications.

[3]  R.S. Parker,et al.  A model-based algorithm for blood glucose control in Type I diabetic patients , 1999, IEEE Transactions on Biomedical Engineering.

[4]  D. Cox,et al.  Symmetrization of the Blood Glucose Measurement Scale and Its Applications , 1997, Diabetes Care.

[5]  F. El-Khatib,et al.  Adaptive Closed-Loop Control Provides Blood-Glucose Regulation Using Dual Subcutaneous Insulin and Glucagon Infusion in Diabetic Swine , 2007, Journal of diabetes science and technology.

[6]  Hai Lin,et al.  Stability and Stabilizability of Switched Linear Systems: A Survey of Recent Results , 2009, IEEE Transactions on Automatic Control.

[7]  Tsuyoshi Hori,et al.  A dual design problem via multiple Lyapunov functions , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[8]  Malgorzata E. Wilinska,et al.  Insulin kinetics in type-1 diabetes: continuous and bolus delivery of rapid acting insulin , 2005, IEEE Transactions on Biomedical Engineering.

[9]  R. Hovorka,et al.  Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes. , 2004, Physiological measurement.

[10]  M. Branicky.  Multiple Lyapunov functions and other analysis tools for switched and hybrid systems , 1998, IEEE Trans. Autom. Control..

[11]  Zhao Zhi-cheng,et al.  An IMC-PID control method with set-point weight , 2006 .

[12]  Robert G. Sutherlin,et al.  A Bihormonal Closed-Loop Artificial Pancreas for Type 1 Diabetes , 2010, Science Translational Medicine.

[13]  A. Morse,et al.  Basic problems in stability and design of switched systems , 1999 .

[14]  F. Cameron,et al.  Preventing hypoglycemia using predictive alarm algorithms and insulin pump suspension. , 2009, Diabetes technology & therapeutics.

[15]  F. El-Khatib,et al.  A Feasibility Study of Bihormonal Closed-Loop Blood Glucose Control Using Dual Subcutaneous Infusion of Insulin and Glucagon in Ambulatory Diabetic Swine , 2009, Journal of diabetes science and technology.

[16]  C. C. Palerm,et al.  Hypoglycemia prediction and detection using optimal estimation. , 2005, Diabetes technology & therapeutics.