Adaptive and Personalized Plasma Insulin Concentration Estimation for Artificial Pancreas Systems.
J Diabetes Sci Technol
; 12(3): 639-649, 2018 05.
Article
em En
| MEDLINE
| ID: mdl-29566547
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.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Pâncreas Artificial
/
Diabetes Mellitus Tipo 1
/
Insulina
/
Modelos Teóricos
Limite:
Adolescent
/
Adult
/
Female
/
Humans
/
Male
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article