Polarization–preservation analysis for robust reflection-mode optical glucose sensing in turbid media

Abstract

Non-invasive optical glucose sensing remains challenging in highly scattering media due to depolarization and absorption interference, and polarization scrambling under multiple scattering conditions. In reflection-mode geometries, polarization signals can contain mixed contributions from different optical mechanisms, which respond differently to glucose concentration and limit the effectiveness of conventional polarization metrics. In this work, polarization-resolved reflection measurements were investigated in skin-equivalent milk-based phantoms using visible illumination at 532 and 660 nm. Linear and circular polarization states were compared over glucose concentrations ranging from 50 to 400 mg dL−1. To quantify polarization preservation under multiple scattering, a polarization–preservation ratio (PPR), derived from co- and cross-polarized circular components, was introduced and evaluated alongside the conventional degree-of-polarization (DOP) metric. Circular polarization combined with PPR exhibited stronger glucose-dependent correlations and improved measurement stability compared with linear polarization, particularly under reflection-mode detection. At 660 nm, the proposed approach maintained high correlation coefficients even under pigment interference, demonstrating improved robustness in turbid environments. These results indicate that polarization–preservation analysis provides a physically consistent and robust sensing strategy for reflection-mode optical glucose detection in scattering-dominant media.

Graphical abstract: Polarization–preservation analysis for robust reflection-mode optical glucose sensing in turbid media

Supplementary files

Article information

Article type
Paper
Submitted
09 Mar 2026
Accepted
08 May 2026
First published
14 May 2026

Analyst, 2026, Advance Article

Polarization–preservation analysis for robust reflection-mode optical glucose sensing in turbid media

H. Hsieh, C. Chang and C. Hsieh, Analyst, 2026, Advance Article , DOI: 10.1039/D6AN00257A

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