Non-Invasive Glucose Monitoring Using Optical Sensors and Machine Learning: A Predictive Model for Nutritional and Health Assessment

Non-Invasive Glucose Monitoring Using Optical Sensors and Machine Learning: A Predictive Model for Nutritional and Health Assessment

Glucose monitoring plays a vital role in maintaining metabolic and nutritional balance. However, invasive methods, while accurate, are often painful and impractical for routine use. This study presents a non-invasive glucose monitoring framework that integrates a high-intensity Superbright optical s...

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Bibliographic Details
Main Authors: Heru Agus Santoso, Nur Setiawati Dewi, Susilo, Arga Dwi Pambudi, Hanif Pandu Suhito, Iman Dehzangi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Convolutional neural network
support vector regression
random forest regression
XGBoost regression
sensor technology
non-invasive glucose monitoring
Online Access:https://ieeexplore.ieee.org/document/11088090/
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