Incorporating the Effect of Behavioral States in Multi-Step Ahead Deep Learning Based Multivariate Predictors for Blood Glucose Forecasting in Type 1 Diabetes

Incorporating the Effect of Behavioral States in Multi-Step Ahead Deep Learning Based Multivariate Predictors for Blood Glucose Forecasting in Type 1 Diabetes

Behavioral factors can affect the blood glucose (BG) levels in people with type 1 diabetes (T1D), therefore, their effects need to be incorporated in blood glucose management for these individuals. Accordingly, in this work, we study the effect of two behavioral states, physical activity (PA) and st...

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Bibliographic Details
Main Authors: Mehrad Jaloli, William Lipscomb, Marzia Cescon
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:BioMedInformatics
Subjects:
blood glucose management
continuous glucose monitoring (CGM)
glucose forecasting
convolutional neural network (CNN)
long short-term memory (LSTM)
physical activity index (PAI)
Online Access:https://www.mdpi.com/2673-7426/2/4/48

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