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Real-Time Monitoring of Breath Biomarkers with A Magnetoelastic Contactless Gas Sensor: A Proof of Concept

remote sensing
gas sensors
breath analysis
magnetoelastic resonance
soft magnets
polyvinylpyrrolidone
nanofibers
humidity
biomarkers
diabetes
Peña A, Aguilera JD, Matatagui D, de la Presa P, Horrillo C, Hernando A, Marín P.
Biosensors. 2022; 12(10):871.
https://doi.org/10.3390/bios12100871

In the quest for effective gas sensors for breath analysis, magnetoelastic resonance-based gas sensors (MEGSs) are remarkable candidates. Thanks to their intrinsic contactless operation, they can be used as non-invasive and portable devices. However, traditional monitoring techniques are bound to slow detection, which hinders their application to fast bio-related reactions. Here we present a method for real-time monitoring of the resonance frequency, with a proof of concept for real-time monitoring of gaseous biomarkers based on resonance frequency. This method was validated with a MEGS based on a Metglass 2826 MB microribbon with a polyvinylpyrrolidone (PVP) nanofiber electrospun functionalization. The device provided a low-noise (RMS = 1.7 Hz), fast (<2 min), and highly reproducible response to humidity (Δf = 46–182 Hz for 17–95% RH), ammonia (Δf = 112 Hz for 40 ppm), and acetone (Δf = 44 Hz for 40 ppm). These analytes are highly important in biomedical applications, particularly ammonia and acetone, which are biomarkers related to diseases such as diabetes. Furthermore, the capability of distinguishing between breath and regular air was demonstrated with real breath measurements. The sensor also exhibited strong resistance to benzene, a common gaseous interferent in breath analysis.

Funding

Author A.P. received funding from grant PRE2019-0875001234, Ministerio de Ciencia e Innovación (MCI), Spain. D.M. received funding from Comfuturo, Consejo Superior de Investigaciones Científicas, Spain. Authors A.P., D.M., P.M. and C.H. received funding from projects RTI2018-095856-B-C21 and RTI2018-095856-B-C22, Ministerio de Ciencia e Innovación, Spain. A.P. and P.M. received funding S2018/NMT-4321, Comunidad de Madrid. J.D.A received funding from Next Generation EU, Ministerio de Trabajo y Economía, Comunidad de Madrid, Spain, Programa Investigo from grant 96-UCM-INV.

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