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Short-term diabetes blood glucose prediction based on blood glucose measurements.

Ståhl, Fredrik LU and Johansson, Rolf LU (2008) 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society In 2008 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 1. p.291-294
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 4-7 mmol/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... (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 4-7 mmol/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 absorbtion of injected insulin from the subcutaneous depots and the glucose subsystem the absorbtion 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 analysed. These models were fitted to real data monitored by a 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 investigated. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
2008 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
volume
1
pages
291 - 294
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
external identifiers
  • pmid:19162650
  • wos:000262404500074
  • scopus:84903876801
ISSN
1557-170X
ISBN
978-1-4244-1814-5
DOI
10.1109/IEMBS.2008.4649147
language
English
LU publication?
yes
id
03fd1465-0a98-4519-bb5d-19bf15279056 (old id 1289358)
date added to LUP
2009-02-06 13:25:12
date last changed
2017-01-01 05:35:14
@inproceedings{03fd1465-0a98-4519-bb5d-19bf15279056,
  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 4-7 mmol/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 absorbtion of injected insulin from the subcutaneous depots and the glucose subsystem the absorbtion 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 analysed. These models were fitted to real data monitored by a 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 investigated.},
  author       = {Ståhl, Fredrik and Johansson, Rolf},
  booktitle    = {2008 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  isbn         = {978-1-4244-1814-5},
  issn         = {1557-170X},
  language     = {eng},
  pages        = {291--294},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Short-term diabetes blood glucose prediction based on blood glucose measurements.},
  url          = {http://dx.doi.org/10.1109/IEMBS.2008.4649147},
  volume       = {1},
  year         = {2008},
}