Advanced

Diabetes mellitus modeling and short-term prediction based on blood glucose measurements.

Ståhl, Fredrik LU and Johansson, Rolf LU (2009) In Mathematical Biosciences 217. p.101-117
Abstract
Insulin-Dependent Diabetes Mellitus (IDDM) is a chronic disease characterized by the inability of the pancreas to produce sufficient amounts of insulin. Daily compensation of the deficiency requires 4-6 insulin injections to be taken daily, the aim of this insulin therapy being to maintain normoglycemia - i.e., a blood glucose level between 4 and 7mmol/l. To determine the quantity and timing of these injections, various different approaches are used. Currently, mostly qualitative and semi-quantitative models and reasoning are used to design such a therapy. Here, an attempt is made to show how system identification and control may be used to estimate predictive quantitative models to be used in design of optimal insulin regimens. The system... (More)
Insulin-Dependent Diabetes Mellitus (IDDM) is a chronic disease characterized by the inability of the pancreas to produce sufficient amounts of insulin. Daily compensation of the deficiency requires 4-6 insulin injections to be taken daily, the aim of this insulin therapy being to maintain normoglycemia - i.e., a blood glucose level between 4 and 7mmol/l. To determine the quantity and timing of these injections, various different approaches are used. Currently, mostly qualitative and semi-quantitative models and reasoning are used to design such a therapy. Here, an attempt is made to show how system identification and control may be used to estimate predictive quantitative models to be used in design of optimal insulin regimens. The system was divided into three subsystems, the insulin subsystem, the glucose subsystem and the insulin-glucose interaction. The insulin subsystem aims to describe the absorption of injected insulin from the subcutaneous depots and the glucose subsystem the absorption of glucose from the gut following a meal. These subsystems were modeled using compartment models and proposed models found in the literature. Several black-box models and grey-box models describing the insulin/glucose interaction were developed and analyzed. These models were fitted to real data monitored by an IDDM patient. Many difficulties were encountered, typical of biomedical systems: Non-uniform and scarce sampling, time-varying dynamics and severe nonlinearities were some of the difficulties encountered during the modeling. None of the proposed models were able to describe the system accurately in all aspects during all conditions. However, all the linear models shared some dynamics. Based on the estimated models, short-term blood glucose predictors for up to two-hour-ahead blood glucose prediction were designed. Furthermore, we explored the issues that arise when applying prediction theory and control to short-term blood glucose prediction. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Mathematical Biosciences
volume
217
pages
101 - 117
publisher
Elsevier
external identifiers
  • wos:000263659100001
  • pmid:19022264
  • scopus:58649116460
ISSN
0025-5564
DOI
10.1016/j.mbs.2008.10.008
language
English
LU publication?
yes
id
01736560-7c8d-49c4-9856-431213ba0cd4 (old id 1271274)
date added to LUP
2009-01-16 13:29:34
date last changed
2017-11-19 04:02:17
@article{01736560-7c8d-49c4-9856-431213ba0cd4,
  abstract     = {Insulin-Dependent Diabetes Mellitus (IDDM) is a chronic disease characterized by the inability of the pancreas to produce sufficient amounts of insulin. Daily compensation of the deficiency requires 4-6 insulin injections to be taken daily, the aim of this insulin therapy being to maintain normoglycemia - i.e., a blood glucose level between 4 and 7mmol/l. To determine the quantity and timing of these injections, various different approaches are used. Currently, mostly qualitative and semi-quantitative models and reasoning are used to design such a therapy. Here, an attempt is made to show how system identification and control may be used to estimate predictive quantitative models to be used in design of optimal insulin regimens. The system was divided into three subsystems, the insulin subsystem, the glucose subsystem and the insulin-glucose interaction. The insulin subsystem aims to describe the absorption of injected insulin from the subcutaneous depots and the glucose subsystem the absorption of glucose from the gut following a meal. These subsystems were modeled using compartment models and proposed models found in the literature. Several black-box models and grey-box models describing the insulin/glucose interaction were developed and analyzed. These models were fitted to real data monitored by an IDDM patient. Many difficulties were encountered, typical of biomedical systems: Non-uniform and scarce sampling, time-varying dynamics and severe nonlinearities were some of the difficulties encountered during the modeling. None of the proposed models were able to describe the system accurately in all aspects during all conditions. However, all the linear models shared some dynamics. Based on the estimated models, short-term blood glucose predictors for up to two-hour-ahead blood glucose prediction were designed. Furthermore, we explored the issues that arise when applying prediction theory and control to short-term blood glucose prediction.},
  author       = {Ståhl, Fredrik and Johansson, Rolf},
  issn         = {0025-5564},
  language     = {eng},
  pages        = {101--117},
  publisher    = {Elsevier},
  series       = {Mathematical Biosciences},
  title        = {Diabetes mellitus modeling and short-term prediction based on blood glucose measurements.},
  url          = {http://dx.doi.org/10.1016/j.mbs.2008.10.008},
  volume       = {217},
  year         = {2009},
}