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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 (2013) In International Journal of Control
Abstract
One of the main limiting factors in improving glucose control for T1DM subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing magnitude and duration of such effects would be useful not only for patients and physicians but also for the development of a controller targeting glycemia regulation. Therefore, in this paper we focus on estimating low-complexity yet physiologically sound and individualized 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... (More)
One of the main limiting factors in improving glucose control for T1DM subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing magnitude and duration of such effects would be useful not only for patients and physicians but also for the development of a controller targeting glycemia regulation. Therefore, in this paper we focus on estimating low-complexity yet physiologically sound and individualized 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)
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author
organization
publishing date
type
Contribution to journal
publication status
submitted
subject
keywords
diabetes mellitus, continuous-time identification
in
International Journal of Control
publisher
Taylor & Francis
ISSN
0020-7179
language
English
LU publication?
yes
id
31f716a3-288c-42fc-a056-5c0aaf1d3bc4 (old id 4076211)
date added to LUP
2013-10-07 09:58:21
date last changed
2016-04-16 12:25:21
@article{31f716a3-288c-42fc-a056-5c0aaf1d3bc4,
  abstract     = {One of the main limiting factors in improving glucose control for T1DM subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing magnitude and duration of such effects would be useful not only for patients and physicians but also for the development of a controller targeting glycemia regulation. Therefore, in this paper we focus on estimating low-complexity yet physiologically sound and individualized 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},
  keyword      = {diabetes mellitus,continuous-time identification},
  language     = {eng},
  publisher    = {Taylor & Francis},
  series       = {International Journal of Control},
  title        = {Identification of individualized empirical models of carbohydrate and insulin effects on T1DM blood glucose dynamics},
  year         = {2013},
}