Selection of Noninvasive Features in Wrist-Based Wearable Sensors to Predict Blood Glucose Concentrations Using Machine Learning Algorithms

Glucose monitoring technologies allow users to monitor glycemic fluctuations (e.g., blood glucose levels). This is particularly important for individuals who have diabetes mellitus (DM). Traditional self-monitoring blood glucose (SMBG) devices require the user to prick their finger and extract a blo...

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Bibliographic Details

Published in:	Sensors
Main Authors:	Brian Bogue-Jimenez, Xiaolei Huang, Douglas Powell, Ana Doblas
Format:	Article
Language:	English
Published:	MDPI AG 2022-05-01
Subjects:	blood glucose self-monitoring diabetes mellitus hyperglycemia machine learning noninvasive glucose
Online Access:	https://www.mdpi.com/1424-8220/22/9/3534