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Authors: Rita Alves 1 ; 2 ; 3 ; João Rodrigues 2 ; Efthymia Ramou 1 ; 3 ; Susana Palma 1 ; 3 ; Ana Roque 1 ; 3 and Hugo Gamboa 2

Affiliations: 1 Associate Laboratory i4HB- Institute for Health and Bioeconomy, School of Science and Technology, NOVA University Lisbon, 2819-516 Caparica, Portugal ; 2 LIBPhys (Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics), Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal ; 3 UCIBIO – Applied Molecular Biosciences Unit, Department of Chemistry, School of Science and Technology, NOVA University Lisbon, 2819-516 Caparica, Portugal

Keyword(s): Electronic Nose, Volatile Organic Compounds, Euclidean Distance, Morphology, Classification.

Abstract: Electronic noses (e-noses) mimic human olfaction, by identifying Volatile Organic Compounds (VOCs). This work presents a novel approach that successfully classifies 11 known VOCs using the signals generated by sensing gels in an in-house developed e-nose. The proposed signals’ analysis methodology is based on the generated signals’ morphology for each VOC since different sensing gels produce signals with different shapes when exposed to the same VOC. For this study, two different gel formulations were considered, and an average f1-score of 84% and 71% was obtained, respectively. Moreover, a standard method in time series classification was used to compare the performances. Even though this comparison reveals that the morphological approach is not as good as the 1-nearest neighbour with euclidean distance, it shows the possibility of using descriptive sentences with text mining techniques to perform VOC classification.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Alves, R.; Rodrigues, J.; Ramou, E.; Palma, S.; Roque, A. and Gamboa, H. (2022). Classification of Volatile Compounds with Morphological Analysis of e-nose Response. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS, ISBN 978-989-758-552-4; ISSN 2184-4305, pages 31-39. DOI: 10.5220/0010827200003123

@conference{biosignals22,
author={Rita Alves. and João Rodrigues. and Efthymia Ramou. and Susana Palma. and Ana Roque. and Hugo Gamboa.},
title={Classification of Volatile Compounds with Morphological Analysis of e-nose Response},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS,},
year={2022},
pages={31-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010827200003123},
isbn={978-989-758-552-4},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS,
TI - Classification of Volatile Compounds with Morphological Analysis of e-nose Response
SN - 978-989-758-552-4
IS - 2184-4305
AU - Alves, R.
AU - Rodrigues, J.
AU - Ramou, E.
AU - Palma, S.
AU - Roque, A.
AU - Gamboa, H.
PY - 2022
SP - 31
EP - 39
DO - 10.5220/0010827200003123