14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper WeB4.3

Lotz, Thomas (Univ. of Canterbury), Chase, J. Geoffrey (Univ. of Canterbury), McAuley, Kirsten A (Univ. of Otago), Lin, Jessica (Univ. of Canterbury), Wong, Jason (Univ. of Canterbury), Hann, Christopher E (Univ. of Canterbury), Andreassen, Steen (Aalborg Univ.)

Integral-Based Identification of a Physiological Insulin and Glucose Model on Euglycaemic Clamp and IVGTT Trials

Scheduled for presentation during the Invited Session "Biomedical Parameter Identification: Methods and Clinical Applications" (WeB4), Wednesday, March 29, 2006, 16:10−16:30, Cummings Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 17, 2018

Keywords Biological Systems, Identification for Control, Model Validation


Modelling can enhance the diagnosis and control of metabolic disorders. Clinical effectiveness demands physiological accuracy, patient specificity and identification with limited data. A two-compartment insulin kinetics model and associated insulin-glucose pharmacodynamics are presented. Similarities with C-peptide kinetics are used to simplify parameter identification. Critical patient specific parameters are identified using a novel convex, integral-based method. The model and methods are validated within physiological ranges using euglycaemic clamp (N=146) and IVGTT data. The mean absolute errors in the resulting glucose and insulin profiles are e_G = 5.9% +/- 6.6% SD and e_I = 6.2% +/- 6.4% SD for the clamps and area under glucose and insulin profiles deviated eA_G = 1.6% and eA_I = 6.7% during IVGTT.