Classification of brain electrophysiological changes in response to colour stimuli

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dc.authoridAlobaidi, May/0000-0002-1212-3281
dc.contributor.authorGoksel Duru, Dilek
dc.contributor.authorAlobaidi, May
dc.date.accessioned2025-02-06T17:58:24Z
dc.date.available2025-02-06T17:58:24Z
dc.date.issued2021
dc.departmentAltınbaş Üniversitesien_US
dc.description.abstractIn this study, the classification of ongoing brain activity occurring as a response to colour stimuli was managed and reported. Until now, the classification of the seen colour from brain electrical signals has not been investigated or reported in the related literature. In this study, we aimed to classify EEG brain responses corresponding to blue, green, and red coloured shapes. In addition to the current literature, we focused on ongoing EEG responses instead of using ERP metrics, with visual stimulus-related ERP metrics also compared throughout the study. The feature extraction process was carried out using the Fourier transform to obtain the conventional band power values of the EEG for each stimulus type. Delta, theta, alpha, beta, and gamma-band power values of each one-second period constituted the feature set. In addition to scalp measurements, a second feature set was obtained based on the inverse solution of the EEG waves. Furthermore, we applied one-way ANOVA for the feature selection prior to classification procedures. Four classifiers were implemented using the reduced feature set and the raw one as well. The differences between scalp responses were localized mainly around the temporal and temporoparietal regions. Our ERP-component findings support the fact that additional brain regions among the visual cortex participate in the colour categorization process of the brain. RGB colours were identified using 1 s EEG data. Ensemble-KNN and KNN achieved the highest accuracy values (93%) when used either with scalp spectral features or source space features.en_US
dc.description.sponsorshipIstanbul Development Agency (ISTKA) [TR10/18/GMP/0032]en_US
dc.description.sponsorshipThe research is partly supported by Istanbul Development Agency (ISTKA) under Project ID TR10/18/GMP/0032.en_US
dc.identifier.doi10.1007/s13246-021-01021-2
dc.identifier.endpage743en_US
dc.identifier.issn2662-4729
dc.identifier.issn2662-4737
dc.identifier.issue3en_US
dc.identifier.pmid34269986
dc.identifier.scopus2-s2.0-85110502426
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage727en_US
dc.identifier.urihttps://doi.org/10.1007/s13246-021-01021-2
dc.identifier.urihttps://hdl.handle.net/20.500.12939/5224
dc.identifier.volume44en_US
dc.identifier.wosWOS:000673259100001
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofPhysical and Engineering Sciences in Medicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKA_WOS_20250206
dc.subjectElectroencephalographyen_US
dc.subjectColour stimulien_US
dc.subjectClassificationen_US
dc.subjectMachine learningen_US
dc.subjectEvent-related potentialsen_US
dc.titleClassification of brain electrophysiological changes in response to colour stimulien_US
dc.typeArticleen_US

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