title: An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods.
abstract: In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.
authors.affiliation: Faculty of Electrical and Computer Engineering, National Technical University of Athens, 9 Heroon Polytechneiou Str. 15780 Zographou, Greece. kzarkog@biosim.ntua.gr
authors.forename: Konstantia
authors.initials: K
authors.lastname: Zarkogianni
authors.forename: Stavroula G
authors.initials: SG
authors.lastname: Mougiakakou
authors.forename: Aikaterini
authors.initials: A
authors.lastname: Prountzou
authors.forename: Andriani
authors.initials: A
authors.lastname: Vazeou
authors.forename: Christos S
authors.initials: CS
authors.lastname: Bartsocas
authors.forename: Konstantina S
authors.initials: KS
authors.lastname: Nikita
mesh_terms: D000465:Algorithms; D001786:Blood Glucose / Q000032:analysis / Q000378:metabolism*; D003198:Computer Simulation; D003922:Diabetes Mellitus, Type 1 / Q000188:drug therapy* / Q000378:metabolism*; D016903:Drug Monitoring / Q000379:methods*; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage; D007328:Insulin / Q000008:administration & dosage*; D007332:Insulin Infusion Systems; D008657:Metabolic Clearance Rate / Q000187:drug effects; D008954:Models, Biological; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D001786:Blood Glucose; D007004:Hypoglycemic Agents; D007328:Insulin