Automatic classification and permittivity estimation of glycerin solutions using a dielectric resonator sensor and Machine Learning techniques

Honrubia, Miguel Monteagudo; Herráiz-Martínez, Francisco Javier; Domingo, Javier Matanza

doi:10.1109/i2mtc53148.2023.10176097

2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) 2023

DOI: 10.1109/i2mtc53148.2023.10176097

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Automatic classification and permittivity estimation of glycerin solutions using a dielectric resonator sensor and Machine Learning techniques

Miguel Monteagudo Honrubia

Francisco Javier Herráiz-Martínez

Javier Matanza Domingo

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2024

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Cited by 1 publication

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Principal Component Regression for Small-Sample Microwave-Microfluidic Chemometrics Without De-Embedding

Mertens,

Martinic,

Markovic

et al. 2024

2024 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)

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Broadband dielectric spectroscopy allows for labelfree analysis of biological material. However, the data can be challenging to interpret. In this work, Principal Component Regression (PCR) is introduced for the concentration extraction of multiple constituents of a liquid using microwave-microfluidics. S-parameters are measured from 0.5 to 18 GHz on a microwavemicrofluidic chip with intentionally introduced error, loaded with solutions having various concentrations of Sodium Chloride (NaCl) and glucose. The mean absolute percentage error for the predictions of the concentration of NaCl and glucose was 2%. It was found that PCR can be used for the prediction of multiple constituents of a liquid with a limited number of training samples, and without needing to de-embed the measurements.

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Principal Component Regression for Small-Sample Microwave-Microfluidic Chemometrics Without De-Embedding

Mertens,

Martinic,

Markovic

et al. 2024

2024 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)

View full text Add to dashboard Cite

show abstract

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Automatic classification and permittivity estimation of glycerin solutions using a dielectric resonator sensor and Machine Learning techniques

Cited by 1 publication

References 19 publications

Principal Component Regression for Small-Sample Microwave-Microfluidic Chemometrics Without De-Embedding

Principal Component Regression for Small-Sample Microwave-Microfluidic Chemometrics Without De-Embedding

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