Non-Invasive Glucose Sensing on Fingertip Using a Mueller Matrix Polarimetry With Machine Learning

Non-Invasive Glucose Sensing on Fingertip Using a Mueller Matrix Polarimetry With Machine Learning

This study achieved significant predictive results using Mueller Matrix Polarimetry combined with the XGBoost algorithm for non-invasive glucose sensing of biological tissues on human fingertips. The experiment used a 660nm laser in polarimetry and incident angle optimization to enhance measurement...

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Bibliographic Details
Main Authors: Chih-Yi Liu, Yu-Lung Lo, Wei-Chun Hung
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Photonics Journal
Subjects:
Mueller matrix polarimetry
XGBoost algorithm
machine learning
blood glucose
non-invasive sensing
Online Access:https://ieeexplore.ieee.org/document/11018343/
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https://ieeexplore.ieee.org/document/11018343/

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