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J Diabetes Sci Technol. 2018 May;12(3):639-649. doi: 10.1177/1932296818763959. Epub 2018 Mar 23.

Adaptive and Personalized Plasma Insulin Concentration Estimation for Artificial Pancreas Systems.

Author information

1
1 Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA.
2
2 Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA.
3
3 Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA.
4
4 School of Information Science and Technology, Northeastern University, Shenyang, China.
5
5 Department of Pediatrics and Medicine, Section of Endocrinology, Kovler Diabetes Center, University of Chicago, Chicago, IL, USA.
6
6 Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA.

Abstract

BACKGROUND:

The artificial pancreas (AP) system, a technology that automatically administers exogenous insulin in people with type 1 diabetes mellitus (T1DM) to regulate their blood glucose concentrations, necessitates the estimation of the amount of active insulin already present in the body to avoid overdosing.

METHOD:

An adaptive and personalized plasma insulin concentration (PIC) estimator is designed in this work to accurately quantify the insulin present in the bloodstream. The proposed PIC estimation approach incorporates Hovorka's glucose-insulin model with the unscented Kalman filtering algorithm. Methods for the personalized initialization of the time-varying model parameters to individual patients for improved estimator convergence are developed. Data from 20 three-days-long closed-loop clinical experiments conducted involving subjects with T1DM are used to evaluate the proposed PIC estimation approach.

RESULTS:

The proposed methods are applied to the clinical data containing significant disturbances, such as unannounced meals and exercise, and the results demonstrate the accurate real-time estimation of the PIC with the root mean square error of 7.15 and 9.25 mU/L for the optimization-based fitted parameters and partial least squares regression-based testing parameters, respectively.

CONCLUSIONS:

The accurate real-time estimation of PIC will benefit the AP systems by preventing overdelivery of insulin when significant insulin is present in the bloodstream.

KEYWORDS:

artificial pancreas; glucose control; hypoglycemia mitigation; insulin on board; plasma insulin concentration

PMID:
29566547
PMCID:
PMC6154239
DOI:
10.1177/1932296818763959
[Indexed for MEDLINE]
Free PMC Article

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