Document Type

Conference Proceeding

Publication Date

3-5-2026

Abstract

The progression of diseases such as cancer has been correlated with tissue stiffness. For example, breast cancer tissue has been found to be stiffer than healthy mammary tissue. At present, stiffness measurement devices are not suitable for nondestructive, high-resolution measurements on small, delicate samples. We report a compact, portable, and sensitive fiber optic stress sensor that overcomes many of these limitations and is suitable for soft materials such as tissue. We demonstrate several improvements to a previous fiber stress sensor in physical hardware, software, and data analysis. We have designed and fabricated a custom enclosure to shield the sensitive setup from air currents and a fixture that allows us to control the tension and angles of the fiber, initial polarization, and the angle of the sensor with respect to the fiber. We also made a Python program to collect and process data all in one place. We demonstrate that only measuring the orthogonal polarization components using two power meters instead of a polarimeter maintains enough information to calculate stress, allowing us to replace the expensive polarimeter with inexpensive and comparatively simple power meters. The data from the power meters is also simpler and faster to process in real time when compared to the polarimeter data. We have validated experimentally that the dual-power meter measurement scheme is consistent with the polarimeter method.

Comments

This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Proceedings of the SPIE Volume 13842, Optical Fibers and Sensors for Medical Diagnostics, Treatment, and Environmental Applications XXVI in 2026. This article may not exactly replicate the final published version. The definitive publisher-authenticated version is available online at https://doi.org/10.1117/12.3080045.

Copyright

Copyright 2026 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

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