Blood Glucose Level Prediction for Diabetics Based on Nutrition and Insulin Administration Logs Using Personalized Mathematical Models
Joint Authors
Vassányi, István
Kósa, István
Gyuk, Péter
Source
Journal of Healthcare Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-01-10
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
According to recent surveys, the current ways of diabetics trying to estimate their insulin need based on experience and conjecture are sometimes inefficient in practice.
This paper proposes a prediction algorithm and presents the validation of the model in outpatient care.
The algorithm consists of two state-of-the-art models that calculate nutrition absorption and glycaemia including insulin evolution.
The combined model is extended with personalized parameter training including genetic algorithm and Nelder–Mead method, and a more realistic, diurnal parameter profile as a representation of the natural biorhythm.
This method implemented in a user-friendly application can help diabetics calculate their insulin need.
The tests were performed on a data set including a clinical trial involving more than 20 diabetic patients.
We experienced 55% improvement in the results due to model training compared to the tests based on literature parameters.
In the best case, 92.5% of the predicted blood glucose level values were in the range of clinically acceptable errors, which means around 2.8 mmol/l root mean square error.
The results of the validation based on outpatient data are promising compared to others found in the literature.
Handling other important factors such as physical activity and stress remains a challenge for future research.
American Psychological Association (APA)
Gyuk, Péter& Vassányi, István& Kósa, István. 2019. Blood Glucose Level Prediction for Diabetics Based on Nutrition and Insulin Administration Logs Using Personalized Mathematical Models. Journal of Healthcare Engineering،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1175413
Modern Language Association (MLA)
Gyuk, Péter…[et al.]. Blood Glucose Level Prediction for Diabetics Based on Nutrition and Insulin Administration Logs Using Personalized Mathematical Models. Journal of Healthcare Engineering No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1175413
American Medical Association (AMA)
Gyuk, Péter& Vassányi, István& Kósa, István. Blood Glucose Level Prediction for Diabetics Based on Nutrition and Insulin Administration Logs Using Personalized Mathematical Models. Journal of Healthcare Engineering. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1175413
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175413