SPR humidity dynamic monitoring method via PVA sensing membrane thickness variation and image processing techniques

Abstract

Humidity monitoring is paramount in diverse applications, industrial, and medical applications. Surface Plasmon Resonance (SPR) is an optical detection technique capable of sensing various environmental parameters through changes in reflected optical spectra and has garnered significant attention. Typically, SPR sensing employs a single-point detection strategy with the sample at a fixed concentration to achieve optimal sensitivity, limiting its application in dynamic environmental testing. This study proposes an image-based SPR humidity monitoring method, integrating SPR with image processing, enabling dynamic parameter reconstruction, and achieving high responsiveness. Au-PVA is used as a sensing film. To attain the best sensing film thickness, sensing film thicknesses ranging from 94.0 $nm$ to 243.3 $nm$ were tested. Through optimizing film thickness and image data processing, high precision and dynamic responsiveness were achieved. Experimental results demonstrate a response time of 84 $ms$ and an average relative prediction error of 1.57 % for the sensor. Our research holds significant promise for dynamic and accurate humidity detection.