Polynomial regression of multiple sensing variables for high-performance smartphone colorimeter
| Autor: | John Canning, Saptami Rani, Rafiqul Islam, Protik Chandra Biswas, Arafat Hossain |
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| Rok vydání: | 2021 |
| Předmět: |
Polynomial regression
CMOS sensor Computer science business.industry System of measurement Colorimeter Detector Sample (graphics) Signal GeneralLiterature_MISCELLANEOUS Atomic and Molecular Physics and Optics Electronic Optical and Magnetic Materials Flash (photography) Electrical and Electronic Engineering business Computer hardware |
| Zdroj: | OSA Continuum. 4:374 |
| ISSN: | 2578-7519 |
| DOI: | 10.1364/osac.417889 |
| Popis: | 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 (λ = 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. |
| Databáze: | OpenAIRE |
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