Research

In silico evaluation of a control system and algorithm for automated insulin infusion in the ICU setting

José L Ortiz¹ , Marcelo W Guarini¹ , Gisella R Borzone³ and Pablo R Olmos^1,2

¹  Department of Electrical Engineering, College of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

²  Department of Nutrition, Diabetes & Metabolism, College of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile

³  Department of Respiratory Diseases, College of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile

author email corresponding author email

BioMedical Engineering OnLine 2010, 9:35doi:10.1186/1475-925X-9-35

Published:	20 July 2010

Abstract

Background

It is known that tight control of glucose in the Intensive Care Unit reduces morbidity and mortality not only in diabetic patients but also in those non-diabetics who become transiently hyperglycemic. Taking advantage of a recently marketed subcutaneous glucose sensor we designed an Automatic Insulin Infusion System (AIIS) for inpatient treatment, and tested its stability under simulated clinical conditions.

Methods

The system included: reference glucose, glucose sensor, insulin and glucose infusion controllers and emergency infusion logic. We carried out computer simulations using Matlab/Simulink^®, in both common and worst-case conditions.

Results

The system was capable of controlling glucose levels without entering in a phase of catastrophic instability, even under severe simulated challenges. Care was taken to include in all simulations the 5-10 minute delay of the subcutaneous glucose signal when compared to the real-time serum glucose signal, a well-known characteristic of all subcutaneous glucose sensors.

Conclusions

When tested in-Silico, a commercially available subcutaneous glucose sensor allowed the stable functioning of a proportional-derivative Automatic Insulin Infusion System, which was able to maintain glucose within acceptable limits when using a well-established glucose response model simulating a patient. Testing of the system in vivo using animal models is now warranted.