A Coupled Insulin and Meal Effect Neuro-Fuzzy Model for The Prediction of Blood Glucose Level in Type 1 Diabetes Mellitus Patients.
Date
2019-07
Authors
Orieke, N.O
Asaolu, O.S
Fashanu, T.A
Fasanmade, O.A
Journal Title
Journal ISSN
Volume Title
Publisher
Sciendo
Abstract
Diabetes Mellitus is a metabolic disorder that affects the ability of the human body to properly utilize and regulate
glucose. It is pervasive world-wide yet tenuous and costly to manage. Diabetes Mellitus is also difficult to model
because it is nonlinear, dynamic and laden with mostly patient specific uncertainties. A neuro-fuzzy model for the
prediction of blood glucose level in Type 1 diabetic patients using coupled insulin and meal effects is developed.
This study establishes that the necessary and sufficient conditions to predict blood glucose level in a Type 1 diabetes
mellitus patient are: knowledge of the patient’s insulin effects and meal effects under diverse metabolic scenarios
and the transparent coupling of the insulin and meal effects. The neuro-fuzzy models were trained with data collected
from a single Type 1 diabetic patient covering a period of two months. Clarke’s Error Grid Analysis (CEGA) of the
model shows that 87.5% of the predictions fall into region A, while the remaining 12.5% of the predictions fall into
region B within a four (4) hour prediction window. The model reveals significant variation in insulin and glucose
responses as the Body Mass Index (BMI) of the patient changes
Description
Staff publications
Keywords
Blood glucose level , Diabetes mellitus , Metabolic disorder , neuro-fuzzy model , Research Subject Categories::MEDICINE
Citation
Orieke NO, Asaolu OS, Fashanu TA, Fasanmade OA. A Coupled Insulin and Meal Effect Neuro-Fuzzy Model for The Prediction of Blood Glucose Level in Type 1 Diabetes Mellitus Patients. Annals of Science and Technology. 2019;4(1):1-15