Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization

The use of electronic noses (eNoses) as analysis tools are growing in popularity; however, the lack of a comprehensive, visual representation of how the different classes are organized and distributed largely complicates the interpretation of the classification results, thus reducing their practical...

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Detalles Bibliográficos
Autores: Palacín Roca, Jordi, Rubies, Elena, Clotet Bellmunt, Eduard
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/84134
Acceso en línea:https://doi.org/10.3390/s22145262
http://hdl.handle.net/10459.1/84134
Access Level:acceso abierto
Palabra clave:Electronic nose
eNose
Array of gas sensors
MOX gas sensors
PCA and LDA analysis
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spelling Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map VisualizationPalacín Roca, JordiRubies, ElenaClotet Bellmunt, EduardElectronic noseeNoseArray of gas sensorsMOX gas sensorsPCA and LDA analysisThe use of electronic noses (eNoses) as analysis tools are growing in popularity; however, the lack of a comprehensive, visual representation of how the different classes are organized and distributed largely complicates the interpretation of the classification results, thus reducing their practicality. The new contributions of this paper are the assessment of the multivariate classification performance of a custom, low-cost eNose composed of 16 single-type (identical) MOX gas sensors for the classification of three volatiles, along with a proposal to improve the visual interpretation of the classification results by means of generating a detailed 2D class-map representation based on the inverse of the orthogonal linear transformation obtained from a PCA and LDA analysis. The results showed that this single-type eNose implementation was able to perform multivariate classification, while the class-map visualization summarized the learned features and how these features may affect the performance of the classification, simplifying the interpretation and understanding of the eNose results.MDPI2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://doi.org/10.3390/s22145262http://hdl.handle.net/10459.1/84134reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)InglésReproducció del document publicat a https://doi.org/10.3390/s22145262Sensors, 2022, vol. 22, núm. 14, 5262cc-by (c) Jordi Palacín, Elena Rubies, Eduard Clotet, 2022info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:repositori.udl.cat:10459.1/841342026-06-24T12:42:17Z
dc.title.none.fl_str_mv Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization
title Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization
spellingShingle Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization
Palacín Roca, Jordi
Electronic nose
eNose
Array of gas sensors
MOX gas sensors
PCA and LDA analysis
title_short Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization
title_full Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization
title_fullStr Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization
title_full_unstemmed Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization
title_sort Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization
dc.creator.none.fl_str_mv Palacín Roca, Jordi
Rubies, Elena
Clotet Bellmunt, Eduard
author Palacín Roca, Jordi
author_facet Palacín Roca, Jordi
Rubies, Elena
Clotet Bellmunt, Eduard
author_role author
author2 Rubies, Elena
Clotet Bellmunt, Eduard
author2_role author
author
dc.subject.none.fl_str_mv Electronic nose
eNose
Array of gas sensors
MOX gas sensors
PCA and LDA analysis
topic Electronic nose
eNose
Array of gas sensors
MOX gas sensors
PCA and LDA analysis
description The use of electronic noses (eNoses) as analysis tools are growing in popularity; however, the lack of a comprehensive, visual representation of how the different classes are organized and distributed largely complicates the interpretation of the classification results, thus reducing their practicality. The new contributions of this paper are the assessment of the multivariate classification performance of a custom, low-cost eNose composed of 16 single-type (identical) MOX gas sensors for the classification of three volatiles, along with a proposal to improve the visual interpretation of the classification results by means of generating a detailed 2D class-map representation based on the inverse of the orthogonal linear transformation obtained from a PCA and LDA analysis. The results showed that this single-type eNose implementation was able to perform multivariate classification, while the class-map visualization summarized the learned features and how these features may affect the performance of the classification, simplifying the interpretation and understanding of the eNose results.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3390/s22145262
http://hdl.handle.net/10459.1/84134
url https://doi.org/10.3390/s22145262
http://hdl.handle.net/10459.1/84134
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a https://doi.org/10.3390/s22145262
Sensors, 2022, vol. 22, núm. 14, 5262
dc.rights.none.fl_str_mv cc-by (c) Jordi Palacín, Elena Rubies, Eduard Clotet, 2022
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv cc-by (c) Jordi Palacín, Elena Rubies, Eduard Clotet, 2022
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Repositori Obert UdL
instname:Universitat de Lleida (UdL)
instname_str Universitat de Lleida (UdL)
reponame_str Repositori Obert UdL
collection Repositori Obert UdL
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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