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Automatic Detection of a Phases for CAP Classification

dc.contributor.authorMendonça, Fábio
dc.contributor.authorFred, Ana
dc.contributor.authorMostafa, Sheikh Shanawaz
dc.contributor.authorDias, Fernando Morgado
dc.contributor.authorRavelo-García, Antonio G.
dc.date.accessioned2024-02-09T12:09:33Z
dc.date.available2024-02-09T12:09:33Z
dc.date.issued2018
dc.description.abstractThe aim of this study is to develop an automatic detector of the cyclic alternating pattern by first detecting the activation phases (A phases) of this pattern, analysing the electroencephalogram during sleep, and then applying a finite state machine to implement the final classification. A public database was used to test the algorithms and a total of eleven features were analysed. Sequential feature selection was employed to select the most relevant features and a post processing procedure was used for further improvement of the classification. The classification of the A phases was produced using linear discriminant analysis and the average accuracy, sensitivity and specificity was, respectively, 75%, 78% and 74%. The cyclic alternating pattern detection accuracy was 75%. When comparing with the state of the art, the proposed method achieved the highest sensitivity but a lower accuracy since the fallowed approach was to keep the REM periods, contrary to the method that is used in the majority of the state of the art publications which leads to an increase in the overall performance. However, the approach of this work is more suitable for automatic system implementation since no alteration of the EEG data is needed.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMendonça, F.; Fred, A.; Shanawaz Mostafa, S.; Morgado-Dias, F. and Ravelo-García, A. (2018). Automatic Detection of a Phases for CAP Classification. In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-276-9; ISSN 2184-4313, SciTePress, pages 394-400. DOI: 10.5220/0006595103940400pt_PT
dc.identifier.doi10.5220/0006595103940400pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/5546
dc.language.isoengpt_PT
dc.publisherSciTePresspt_PT
dc.relationLaboratory for Robotics and Engineering Systems
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectA phasept_PT
dc.subjectCyclic alternating patternpt_PT
dc.subjectCAPpt_PT
dc.subjectLDApt_PT
dc.subject.pt_PT
dc.subjectEscola Superior de Tecnologias e Gestãopt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.titleAutomatic Detection of a Phases for CAP Classificationpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleLaboratory for Robotics and Engineering Systems
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F50009%2F2013/PT
oaire.citation.endPage400pt_PT
oaire.citation.startPage394pt_PT
oaire.citation.titleProceedings of the 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018), p. 394-400, (Enero 2018)pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameSilva Mendonça
person.familyNameMostafa
person.familyNameMorgado-Dias
person.familyNameRavelo-García
person.givenNameFábio Rúben
person.givenNameSheikh Shanawaz
person.givenNameFernando
person.givenNameAntonio G.
person.identifier34497
person.identifier.ciencia-id7F1E-8AE9-3098
person.identifier.ciencia-idEE14-BEB3-F82B
person.identifier.ciencia-id7B14-DF07-AA6D
person.identifier.orcid0000-0002-5107-3248
person.identifier.orcid0000-0002-7677-0971
person.identifier.orcid0000-0001-7334-3993
person.identifier.orcid0000-0002-8512-965X
person.identifier.ridN-9228-2015
person.identifier.scopus-author-id55489640900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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