Parameter Estimation in Type 2 Diabetes in the Presence of Unannounced Meals and Unmodelled Disturbances

Mohamad Al Ahdab*, Henrik Glavind Clausen, Torben Knudsen, Tinna Björk Araddóttir, Signe Schmidt, Kirsten Nørgaard, John-Josef Leth

*Corresponding author

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

A least squares strategy to estimate states and parameters
for type 2 diabetes (T2D) patients based only on continuous
glucose measurements and injected insulin in the presence
of unannounced meals and disturbances, e.g., physical
activity and stress, is presented. The strategy is based on
a simple T2D patient model and tested with clinical data in
addition to simulated data generated by using jump
diffusion models for meals and disturbances. Three
parameters are estimated together with the states, meals,
and disturbances. The estimated meal states were shown to
follow the trend of the unannounced meals. The strategy can
be used to obtain a model with the estimated parameters for
predictive control design. In addition, the strategy can
also be used to test different insulin and meal plans with
the estimated disturbances and parameters. Moreover, the
paper demonstrates the ability of jump diffusion models to
simulate meals and disturbances.
Original languageEnglish
Title of host publication20th 2021 European Control Conference (ECC)
PublisherIEEE
Publication statusAccepted/In press - 2021

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