title: Active insulin infusion using optimal and derivative-weighted control.
abstract: Close control of blood glucose levels significantly reduces vascular complications in Type I diabetes. A control method for the automation of insulin infusion that utilizes emerging technologies in blood glucose biosensors is presented. The controller developed provides tighter, more optimal control of blood glucose levels, while accounting for variation in patient response, insulin employed and sensor bandwidth. Particular emphasis is placed on controller simplicity and robustness necessary for medical devices and implants.A PD controller with heavy emphasis on the derivative term is found to outperform the typically used proportional-weighted controllers in glucose tolerance and multi-meal tests. Simulation results show reductions of over 50% in the magnitude and duration of blood glucose excursions from basal levels. A closed-form steady state optimal solution is also developed as a benchmark, and results in a flat glucose response. The impact and trade-offs associated with sensor bandwidth, sensor lag and proportional versus derivative-based control methods are illustrated. Overall, emerging blood glucose sensor technologies that enable frequent measurement are shown to enable more effective, automated control of blood glucose levels within a tight, acceptable range for Type I and II diabetic individuals.
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand.
authors.forename: Z-H
authors.initials: ZH
authors.lastname: Lam
authors.forename: K-S
authors.initials: KS
authors.lastname: Hwang
authors.forename: J-Y
authors.initials: JY
authors.lastname: Lee
authors.forename: J G
authors.initials: JG
authors.lastname: Chase
authors.forename: G C
authors.initials: GC
authors.lastname: Wake
mesh_terms: D001786:Blood Glucose / Q000378:metabolism; D003198:Computer Simulation; D003922:Diabetes Mellitus, Type 1 / Q000188:drug therapy*; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D004867:Equipment Design; D019544:Equipment Failure Analysis / Q000379:methods; D005246:Feedback; D005951:Glucose Tolerance Test / Q000379:methods; D006801:Humans; D007328:Insulin / Q000008:administration & dosage*; D007332:Insulin Infusion Systems; D008954:Models, Biological; D011786:Quality Control
chemical_list: D001786:Blood Glucose; D007328:Insulin