Identification of Individualized Empirical Models of Carbohydrate and Insulin Effects on T1DM Blood Glucose Dynamics
Cescon, Marzia LU ; Johansson, Rolf LU
; Renard, Eric
and Maran, Alberto
(2014)
In International Journal of Control
87(7).
p.1438-1453
- Abstract
- One of the main limiting factors in improving glucose control for type 1 diabetes mellitus (T1DM) subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing the magnitude and duration of such effects would be useful not only for patients and physicians, but also for the development of a controller targeting glycaemia regulation. Therefore, in this paper we focus on estimating low-complexity yet physiologically sound and individualised multi-input single-output (MISO) models of the glucose metabolism in T1DM able to reflect the basic dynamical features of the glucose-insulin metabolic system in response to a meal intake or an insulin injection. The models are continuous-time second-order... (More)
- One of the main limiting factors in improving glucose control for type 1 diabetes mellitus (T1DM) subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing the magnitude and duration of such effects would be useful not only for patients and physicians, but also for the development of a controller targeting glycaemia regulation. Therefore, in this paper we focus on estimating low-complexity yet physiologically sound and individualised multi-input single-output (MISO) models of the glucose metabolism in T1DM able to reflect the basic dynamical features of the glucose-insulin metabolic system in response to a meal intake or an insulin injection. The models are continuous-time second-order transfer functions relating the amount of carbohydrate of a meal and the insulin units of the accordingly administered dose (inputs) to plasma glucose evolution (output) and consist of few parameters clinically relevant to be estimated. The estimation strategy is continuous-time data-driven system identification and exploits a database in which meals and insulin boluses are separated in time, allowing the unique identification of the model parameters. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4558824
- author
- Cescon, Marzia
LU
; Johansson, Rolf
LU
; Renard, Eric
and Maran, Alberto
- organization
- publishing date
- 2014
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- metabolic systems, diabetic blood glucose dynamics, linear systems, continuous-time identification
- in
- International Journal of Control
- volume
- 87
- issue
- 7
- pages
- 16 pages
- publisher
- Taylor & Francis
- external identifiers
-
- wos:000335853100009
- scopus:84901001437
- ISSN
- 0020-7179
- DOI
- 10.1080/00207179.2014.883171
- project
- DIAdvisor
- language
- English
- LU publication?
- yes
- id
- 94433776-1e34-4b2e-8548-01a154685a13 (old id 4558824)
- date added to LUP
- 2016-04-01 11:15:26
- date last changed
- 2023-09-04 12:16:35
@article{94433776-1e34-4b2e-8548-01a154685a13,
abstract = {{One of the main limiting factors in improving glucose control for type 1 diabetes mellitus (T1DM) subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing the magnitude and duration of such effects would be useful not only for patients and physicians, but also for the development of a controller targeting glycaemia regulation. Therefore, in this paper we focus on estimating low-complexity yet physiologically sound and individualised multi-input single-output (MISO) models of the glucose metabolism in T1DM able to reflect the basic dynamical features of the glucose-insulin metabolic system in response to a meal intake or an insulin injection. The models are continuous-time second-order transfer functions relating the amount of carbohydrate of a meal and the insulin units of the accordingly administered dose (inputs) to plasma glucose evolution (output) and consist of few parameters clinically relevant to be estimated. The estimation strategy is continuous-time data-driven system identification and exploits a database in which meals and insulin boluses are separated in time, allowing the unique identification of the model parameters.}},
author = {{Cescon, Marzia and Johansson, Rolf and Renard, Eric and Maran, Alberto}},
issn = {{0020-7179}},
keywords = {{metabolic systems; diabetic blood glucose dynamics; linear systems; continuous-time identification}},
language = {{eng}},
number = {{7}},
pages = {{1438--1453}},
publisher = {{Taylor & Francis}},
series = {{International Journal of Control}},
title = {{Identification of Individualized Empirical Models of Carbohydrate and Insulin Effects on T1DM Blood Glucose Dynamics}},
url = {{http://dx.doi.org/10.1080/00207179.2014.883171}},
doi = {{10.1080/00207179.2014.883171}},
volume = {{87}},
year = {{2014}},
}