Hydration level estimation and classification using a capacitive sensor
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Abstract
This work presents a solution for non-invasive hydration assessment, addressing the critical need for user-friendly methods to replace invasive clinical techniques and ensure proper hydration across diversepopulations. We propose using capacitive sensing, specifically the FDC2114 module equipped with two capacitive sensors, to estimate hydration levels. Inspired by the capacitance changes when a finger is placed on a phone screen, our future vision aims to integrate this technology into smartphones for easy hydration monitoring. The methodology involves data collection, preprocessing, classification algorithms, and data augmentation, followed by neural network analysis.
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Mémoire de Projet de Fin d’Études : Electronique : Alger, École Nationale Polytechnique : 2024