Model Predictive Control of blood glucose in Type 1 diabetes: the Principal Dynamic Modes approach.
This computational study demonstrates the efficacy of regulating blood glucose in Type 1 diabetics with a Model Predictive Control strategy, utilizing a nonparametric / Principal Dynamic Modes model. For this purpose, a stochastic glucose disturbance signal is introduced and a simple methodology for predicting its future values is developed. The results of our simulations confirm that the proposed algorithm achieves very good performance, is computationally efficient and avoids hypoglycaemic events.
Markakis
Mihalis G
MG
Electrical Engineering&Computer Science Department, Massachusetts Institute of Technology, USA. mihalis@mit.edu
Mitsis
Georgios D
GD
Papavassilopoulos
George P
GP
Marmarelis
Vasilis Z
VZ
D001786:Blood Glucose / Q000378:metabolism*; D003198:Computer Simulation; D003922:Diabetes Mellitus, Type 1 / Q000188:drug therapy* / Q000378:metabolism*; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage; D007275:Injections, Intravenous; D007328:Insulin / Q000008:administration & dosage* / Q000097:blood*; D008657:Metabolic Clearance Rate / Q000187:drug effects; D008954:Models, Biological; D015398:Signal Transduction / Q000187:drug effects
D001786:Blood Glucose; D007004:Hypoglycemic Agents; D007328:Insulin