Estimation of insulin sensitivity in diabetic Göttingen Minipigs |
| |
Affiliation: | 1. Philips Chair for Medical Information Technology, RWTH Aachen University, Aachen, Germany;2. Abiomed Europe GmbH, Aachen 52074, Germany;3. Endocrine Research, Bergmannsheil University Hospitals, Ruhr University of Bochum, Bochum 44789, Germany;1. University of Bayreuth, Mathematical Institute, Germany;2. Ruhr-University Bochum, Institute of Automation and Computer Control, Germany;1. Department of Mechanical Engineering, Melbourne University, Australia;2. Defence Science and Technology Group, Melbourne, Australia;1. University “Politehnica” of Bucharest, Faculty of Aerospace Engineering, Str. Polizu, No. 1, 011063, Bucharest, Romania;2. Control Department, IMI Advanced Systems Div., P.O.B. 1044/77, Ramat Hasharon, 47100, Israel |
| |
Abstract: | In patients with type 1 diabetes mellitus, insulin sensitivity is a parameter which strongly affects insulin therapy. Due to its time-dependent variation, this parameter can improve the strategy for automatic closed-loop blood glucose control. The aim of this work is to estimate the insulin sensitivity of patients with type 1 diabetes mellitus based on measured blood glucose concentrations. For this, an Extended Kalman Filter is used, based on a simplified version of the well-known Sorensen model. The compartment model of Sorensen was adapted to the glucose metabolic behaviour in diabetic Göttingen Minipigs by means of experimental data and reduced by neglecting unobservable state variables. Here, the Extended Kalman Filter is designed for simultaneous state and parameter estimation of insulin sensitivity using the insulin infusion rate and the meal size as input signals, and measurements of blood glucose concentration as output signal. The performance of the Extended Kalman Filter was tested in in silico studies using the minipig model, and is analysed by comparing the output signal of the filter with measurement data from the animal trials. |
| |
Keywords: | Type 1 diabetes mellitus Extended Kalman filter Nonlinear dynamics State estimation Göttingen Minipigs |
本文献已被 ScienceDirect 等数据库收录! |
|