Global Sensitivity Analysis on the Bergman Minimal Model

Souransu Nandi; Tarunraj Singh

doi:10.1016/j.ifacol.2020.12.431

Global Sensitivity Analysis on the Bergman Minimal Model

Souransu Nandi
, Tarunraj Singh

Department of Mechanical and Aerospace Engineering

SUNY Buffalo

Research output: Contribution to journal › Conference article › peer-review

7 Scopus citations

Abstract

In this paper, a novel Global Sensitivity Analysis method is developed and is illustrated on the popular Bergman minimal model for Type 1 Diabetes (T1D). Four parameters are assumed to be uncertain in the model to mimic patient variability. An algorithm is presented to evaluate sensitivity metrics by which the uncertain parameters can be ranked. Results reveal that for a single meal scenario, insulin sensitivity is one of the most important factors after the consumption of meal that influences the blood glucose concentration in people with T1D.

Original language	English
Pages (from-to)	16112-16118
Number of pages	7
Journal	IFAC-PapersOnLine
Volume	53
Issue number	2
DOIs	https://doi.org/10.1016/j.ifacol.2020.12.431
State	Published - 2020
Event	21st IFAC World Congress 2020 - Berlin, Germany Duration: Jul 12 2020 → Jul 17 2020

Keywords

Insulin Sensitivity
Polynomial Chaos
Sensitivity Analysis
Sobol Indices

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10.1016/j.ifacol.2020.12.431

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title = "Global Sensitivity Analysis on the Bergman Minimal Model",

abstract = "In this paper, a novel Global Sensitivity Analysis method is developed and is illustrated on the popular Bergman minimal model for Type 1 Diabetes (T1D). Four parameters are assumed to be uncertain in the model to mimic patient variability. An algorithm is presented to evaluate sensitivity metrics by which the uncertain parameters can be ranked. Results reveal that for a single meal scenario, insulin sensitivity is one of the most important factors after the consumption of meal that influences the blood glucose concentration in people with T1D.",

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AU - Singh, Tarunraj

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AB - In this paper, a novel Global Sensitivity Analysis method is developed and is illustrated on the popular Bergman minimal model for Type 1 Diabetes (T1D). Four parameters are assumed to be uncertain in the model to mimic patient variability. An algorithm is presented to evaluate sensitivity metrics by which the uncertain parameters can be ranked. Results reveal that for a single meal scenario, insulin sensitivity is one of the most important factors after the consumption of meal that influences the blood glucose concentration in people with T1D.

KW - Insulin Sensitivity

KW - Polynomial Chaos

KW - Sensitivity Analysis

KW - Sobol Indices

UR - https://www.scopus.com/pages/publications/85119612222

U2 - 10.1016/j.ifacol.2020.12.431

DO - 10.1016/j.ifacol.2020.12.431

M3 - Conference article

AN - SCOPUS:85119612222

SN - 2405-8971

VL - 53

SP - 16112

EP - 16118

JO - IFAC-PapersOnLine

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IS - 2

T2 - 21st IFAC World Congress 2020

Y2 - 12 July 2020 through 17 July 2020

ER -

Global Sensitivity Analysis on the Bergman Minimal Model

Abstract

Keywords

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