Short Term Blood Glucose Prediction based on Continuous Glucose Monitoring Data

Ali Mohebbi, Alexander R. Johansen, Nicklas Hansen, Peter E. Christensen, Jens M. Tarp, Morten L. Jensen, Henrik Bengtsson, Morten Morup

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

12 Downloads (Pure)

Abstract

Continuous Glucose Monitoring (CGM) has enabled important opportunities for diabetes management. This study explores the use of CGM data as input for digital decision support tools. We investigate how Recurrent Neural Networks (RNNs) can be used for Short Term Blood Glucose (STBG) prediction and compare the RNNs to conventional time-series forecasting using Autoregressive Integrated Moving Average (ARIMA). A prediction horizon up to 90 min into the future is considered. In this context, we evaluate both population-based and patient-specific RNNs and contrast them to patient-specific ARIMA models and a simple baseline predicting future observations as the last observed. We find that the population-based RNN model is the best performing model across the considered prediction horizons without the need of patient-specific data. This demonstrates the potential of RNNs for STBG prediction in diabetes patients towards detecting/mitigating severe events in the STBG, in particular hypoglycemic events. However, further studies are needed in regards to the robustness and practical use of the investigated STBG prediction models.

Original languageEnglish
Title of host publicationProceedings of 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society : Enabling Innovative Technologies for Global Healthcare, EMBC 2020
PublisherIEEE
Publication dateJul 2020
Pages5140-5145
Article number9176695
ISBN (Electronic)9781728119908
DOIs
Publication statusPublished - Jul 2020
Event42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society - EMBS Virtual Academy, Montreal, Canada
Duration: 20 Jul 202024 Jul 2020

Conference

Conference42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society
LocationEMBS Virtual Academy
CountryCanada
CityMontreal
Period20/07/202024/07/2020
SeriesProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2020-July
ISSN1557-170X

Fingerprint Dive into the research topics of 'Short Term Blood Glucose Prediction based on Continuous Glucose Monitoring Data'. Together they form a unique fingerprint.

Cite this