TY - JOUR
T1 - A therapy parameter-based model for predicting blood glucose concentrations in patients with type 1 diabetes
AU - Bock, Alain
AU - François, Grégory
AU - Gillet, Denis
PY - 2015
Y1 - 2015
N2 - In this paper, the problem of predicting blood glucose concentrations (BG) for the treatment of patients with type 1 diabetes, is addressed. Predicting BG is of very high importance as most treatments, which consist in exogenous insulin injections, rely on the availability of BG predictions. Many models that can be used for predicting BG are available in the literature. However, it is widely admitted that it is almost impossible to perfectly model blood glucose dynamics while still being able to identify model parameters using only blood glucose measurements. The main contribution of this work is to propose a simple and identifiable linear dynamical model, which is based on the static prediction model of standard therapy. It is shown that the model parameters are intrinsically correlated with physician-set therapy parameters and that the reduction of the number of model parameters to identify leads to inferior data fits but to equivalent or slightly improved prediction capabilities compared to state-of-the-art models: a sign of an appropriate model structure and superior reliability. The validation of the proposed dynamic model is performed using data from the UVa simulator and real clinical data, and potential uses of the proposed model for state estimation and BG control are discussed.
AB - In this paper, the problem of predicting blood glucose concentrations (BG) for the treatment of patients with type 1 diabetes, is addressed. Predicting BG is of very high importance as most treatments, which consist in exogenous insulin injections, rely on the availability of BG predictions. Many models that can be used for predicting BG are available in the literature. However, it is widely admitted that it is almost impossible to perfectly model blood glucose dynamics while still being able to identify model parameters using only blood glucose measurements. The main contribution of this work is to propose a simple and identifiable linear dynamical model, which is based on the static prediction model of standard therapy. It is shown that the model parameters are intrinsically correlated with physician-set therapy parameters and that the reduction of the number of model parameters to identify leads to inferior data fits but to equivalent or slightly improved prediction capabilities compared to state-of-the-art models: a sign of an appropriate model structure and superior reliability. The validation of the proposed dynamic model is performed using data from the UVa simulator and real clinical data, and potential uses of the proposed model for state estimation and BG control are discussed.
KW - Blood glucose control
KW - Blood glucose prediction
KW - Physiological model
KW - Therapy parameters
KW - Type 1 diabetes mellitus
UR - http://www.scopus.com/inward/record.url?scp=84922477053&partnerID=8YFLogxK
U2 - 10.1016/j.cmpb.2014.12.002
DO - 10.1016/j.cmpb.2014.12.002
M3 - Article
C2 - 25577673
AN - SCOPUS:84922477053
VL - 118
SP - 107
EP - 123
JO - Computer methods and programs in biomedicine
JF - Computer methods and programs in biomedicine
SN - 0169-2607
IS - 2
ER -