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Finding the optimal time window for increased classification accuracy during motor imagery

2021Conference object Open access
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dc.contributor.authorBlanco-Mora, D. A.
dc.contributor.authorAldridge, A.
dc.contributor.authorJorge, C.
dc.contributor.authorVourvopoulos, A.
dc.contributor.authorFigueiredo, P.
dc.contributor.authorBermúdez i Badia, S.
dc.date.accessioned2022-07-21T15:31:30Z
dc.date.available2022-07-21T15:31:30Z
dc.date.issued2021
dc.description.abstractMotor imagery classification using electroencephalography is based on feature extraction over a length of time, and different configurations of settings can alter the performance of a classifier. Nevertheless, there is a lack of standardized settings for motor imagery classification. This work analyzes the effect of age on motor imagery training performance for two common spatial pattern-based classifier pipelines and various configurations of timing parameters, such as epochs, windows, and offsets. Results showed significant (p ≤ 0.01) inverse correlations between performance and feature quantity, as well as between performance and epoch/window ratio.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBlanco-Mora, D. A., Aldridge, A., Vieira, C. J., Vourvopoulos, A., Figueiredo, P., & i Badia, S. B. (2021). Finding the optimal time window for increased classification accuracy during motor imagery. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, (pp. 144-151).pt_PT
dc.identifier.doi10.5220/0010316101440151pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/4448
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSciTePreesspt_PT
dc.relationStroke Neurorehabilitation Augmented by Virtual Reality and EEG-neurofeedback: Neuroimaging-based Validation and Optimization
dc.relationNOVA Laboratory for Computer Science and Informatics
dc.relationLaboratory of Robotics and Engineering Systems
dc.relationNot Available
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectBrain-computer interfacept_PT
dc.subjectBCIpt_PT
dc.subjectMotor imagerypt_PT
dc.subjectMIpt_PT
dc.subjectLassification accuracypt_PT
dc.subjectCommon spatial patternpt_PT
dc.subjectCSPpt_PT
dc.subjectElectroencephalographypt_PT
dc.subjectEEGpt_PT
dc.subjectNeurorehabilitationpt_PT
dc.subjectStrokept_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.titleFinding the optimal time window for increased classification accuracy during motor imagerypt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleStroke Neurorehabilitation Augmented by Virtual Reality and EEG-neurofeedback: Neuroimaging-based Validation and Optimization
oaire.awardTitleNOVA Laboratory for Computer Science and Informatics
oaire.awardTitleLaboratory of Robotics and Engineering Systems
oaire.awardTitleNot Available
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FCCI-COM%2F31485%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FCEC%2F04516%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50009%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC IND 2018/CEECIND%2F01073%2F2018%2FCP1572%2FCT0013/PT
oaire.citation.endPage151pt_PT
oaire.citation.startPage144pt_PT
oaire.citation.titleProceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologiespt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamCEEC IND 2018
person.familyNameBlanco Mora
person.familyNameAldridge
person.familyNameJorge
person.familyNameVourvopoulos
person.familyNameFigueiredo
person.familyNameBermúdez i Badia
person.givenNameDiego Andres
person.givenNameAudrey
person.givenNameCarolina
person.givenNameAthanasios
person.givenNamePatricia
person.givenNameSergi
person.identifier279446
person.identifier239789
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person.identifier.orcid0000-0003-2232-0999
person.identifier.orcid0000-0003-3733-4736
person.identifier.orcid0000-0002-7693-7292
person.identifier.orcid0000-0001-9676-8599
person.identifier.orcid0000-0002-0743-0869
person.identifier.orcid0000-0003-4452-0414
person.identifier.ridC-7778-2018
person.identifier.ridF-3872-2017
person.identifier.ridA-1194-2013
person.identifier.ridC-8681-2018
person.identifier.scopus-author-id48762198300
person.identifier.scopus-author-id7003529050
person.identifier.scopus-author-id6506360007
project.funder.identifierhttp://doi.org/10.13039/501100001871
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project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
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