Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/86627
Title: Personalized glucose-insulin model based on signal analysis
Authors: Goede, Simon L.
de Galan, Bastiaan E.
Leow, Melvin Khee Shing
Keywords: Appearance Profile
Model Identification
Issue Date: 2017
Source: Goede, S. L., de Galan, B. E., & Leow, M. K. S. (2017). Personalized glucose-insulin model based on signal analysis. Journal of Theoretical Biology, 419, 333-342.
Series/Report no.: Journal of Theoretical Biology
Abstract: Glucose plasma measurements for diabetes patients are generally presented as a glucose concentration-time profile with 15–60 min time scale intervals. This limited resolution obscures detailed dynamic events of glucose appearance and metabolism. Measurement intervals of 15 min or more could contribute to imperfections in present diabetes treatment. High resolution data from mixed meal tolerance tests (MMTT) for 24 type 1 and type 2 diabetes patients were used in our present modeling. We introduce a model based on the physiological properties of transport, storage and utilization. This logistic approach follows the principles of electrical network analysis and signal processing theory. The method mimics the physiological equivalent of the glucose homeostasis comprising the meal ingestion, absorption via the gastrointestinal tract (GIT) to the endocrine nexus between the liver, pancreatic alpha and beta cells. This model demystifies the metabolic ‘black box’ by enabling in silico simulations and fitting of individual responses to clinical data. Five-minute intervals MMTT data measured from diabetic subjects result in two independent model parameters that characterize the complete glucose system response at a personalized level. From the individual data measurements, we obtain a model which can be analyzed with a standard electrical network simulator for diagnostics and treatment optimization. The insulin dosing time scale can be accurately adjusted to match the individual requirements of characterized diabetic patients without the physical burden of treatment
URI: https://hdl.handle.net/10356/86627
http://hdl.handle.net/10220/44149
ISSN: 0022-5193
DOI: 10.1016/j.jtbi.2016.12.018
Rights: © 2017 Elsevier Ltd. This is the author created version of a work that has been peer reviewed and accepted for publication by Journal of Theoretical Biology, Elsevier Ltd. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.jtbi.2016.12.018].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:LKCMedicine Journal Articles

Files in This Item:
File Description SizeFormat 
Personalized Glucose-Insulin Model based on Signal Analysis.pdf964.54 kBAdobe PDFThumbnail
View/Open

SCOPUSTM   
Citations 20

1
checked on Aug 31, 2020

WEB OF SCIENCETM
Citations 20

1
checked on Oct 26, 2020

Page view(s) 20

96
checked on Oct 28, 2020

Download(s) 20

77
checked on Oct 28, 2020

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.