Polynomial Regression Of Multiple Sensing Variables For High-Performance Smartphone Colorimeter

A robust and adaptive smartphone-based colorimetric sensing platform is reported. It utilizes multiple regression analysis to address nonlinear concurrent variations of multiple sensing variables. The instrument can perform colorimetric measurement with improved accuracy over a wide range where both color and intensity information of a colorimetric signal varies independently often simultaneously. The instrument utilizes the smartphone in-built flash LED (lambda = 400-700 nm) to illuminate the test sample and the phone's CMOS camera as a detector, collecting and digitizing the reflected light from that sample. 3D printing technology is used to fabricate a specially designed optical enclosure that performs as a diffuser, neutral density filter, and reflector to ensure constant and uniform illumination of the sensing platform. Thus, an ultra-low-cost (< 3 USD) portable smartphone-based colorimetric diagnostic system becomes feasible along with an easy-to-use customized android app adaptable for multi-analyte assays. The performance of the colorimetric measurement system is validated by: (a) monitoring the concentration of a laser dye, (b) measuring the pH of drinking water, and (c) quantifying the chlorine concentration of shrimp ponds. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement