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Low-cost RFID-based Sensor Integrated in Textile for Non-Invasive Pervasive Hydration Monitoring

Health monitoring during physical exercise is relevant to avoid issues like dehydration, specially for vulnerable population or in warm climates, since it may become critical in these cases. Current dehydration monitoring solutions are not intended for the general population, since they are expensiv...

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Bibliographic Details
Published in:IEEE sensors journal 2023, p.1-1
Main Authors: Melia-Segui, Joan, Bhattacharyya, Rahul, Lopez-Soriano, Sergio, Vilajosana, Xavier, Sarma, Sanjay E.
Format: Article
Language:English
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Summary:Health monitoring during physical exercise is relevant to avoid issues like dehydration, specially for vulnerable population or in warm climates, since it may become critical in these cases. Current dehydration monitoring solutions are not intended for the general population, since they are expensive or require the action of wearing the device. Hence, a cost-efficient monitoring technology that could be integrated into everyday clothing would allow the democratization of eHealth, and thus, improving the health of the general population. We have been researching on low-cost sensing technologies, allowing the detection of dehydration, while maximizing the trade-off between functionality and cost. In this paper, we present a passive antenna-based UHF RFID sensor, allowing non-invasive dehydration monitoring on fabrics at low-cost. We determine that the dielectric relative permittivity (ε′ r ) and loss tangent (tan(δ)) values exhibit a change up to 10 and 0.3 respectively in the presence of euhydrated (i.e. regular hydration) and dehydrated sweat in the UHF band. We use these results to design a UHF RFID tag attached to a fabric, capable of differentiating between these hydration states. After prototype implementation, we demonstrated good classification metrics at laboratory environment, reaching a 100% accuracy using K-means unsupervised learning when attempting to differentiate between euhydrated and dehydrated sweat in fabrics with concentrations over 58%. To the best of our knowledge, this combination of results is presented for the first time in the literature. Our results demonstrate the feasibility of detecting dehydration at low-cost in an unassisted manner, and thus, the possibility of democratizing eHealth for the general population.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2023.3339117