Classification of Volatile Compounds with Morphological Analysis of e-nose Response

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.
Original languageEnglish
Title of host publicationBIOSIGNALS: Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies – Vol. 4: BIOSIGNALS
EditorsA. Tsanas, A. Fred, Hugo Gamboa
PublisherSciTePress - Science and Technology Publications
Pages31-39
ISBN (Print)978-989-758-552-4
DOIs
Publication statusPublished - 2022
Event15th International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS) held as part of 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) - Online
Duration: 9 Feb 202211 Feb 2022

Conference

Conference15th International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS) held as part of 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC)
CityOnline
Period9/02/2211/02/22

Keywords

  • Electronic Nose
  • Volatile Organic Compounds
  • Euclidean Distance
  • Morphology
  • Classification

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