Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/8913
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dc.contributor.authorOlcay, Bilal Orkan-
dc.contributor.authorKaraçalı, Bilge-
dc.date.accessioned2020-07-18T08:34:07Z-
dc.date.available2020-07-18T08:34:07Z-
dc.date.issued2019-
dc.identifier.issn0010-4825-
dc.identifier.issn1879-0534-
dc.identifier.urihttps://doi.org/10.1016/j.compbiomed.2019.103441-
dc.identifier.urihttps://hdl.handle.net/11147/8913-
dc.description.abstractDuring cognitive, perceptual and sensory tasks, connectivity profile changes across different regions of the brain. Variations of such connectivity patterns between different cognitive tasks can be evaluated using pairwise synchronization measures applied to electrophysiological signals, such as electroencephalography (EEG). However, connectivity-based task recognition approaches achieving viable recognition performance have been lacking from the literature. By using several synchronization measures, we identify time lags between channel pairs during different cognitive tasks. We employed mutual information, cross correntropy, cross correlation, phase locking value, cosine similarity and nonlinear interdependence measures. In the training phase, for each type of cognitive task, we identify the time lags that maximize the average synchronization between channel pairs. These lags are used to calculate pairwise synchronization values with which we construct the train and test feature vectors for recognition of the cognitive task carried out using Fisher's linear discriminant (FLD) analysis. We tested our framework in a motor imagery activity recognition scenario on PhysioNet Motor Movement/Imagery and BCI Competition-III IVa datasets. For PhysioNet dataset, average performance results ranging between % 51 and % 61 across 20 subjects. For BCI Competition-III dataset, we achieve an average recognition performance of % 76 which is above the minimum reliable communication rate (% 70). We achieved an average accuracy over the minimum reliable communication rate on the BCI Competition-III dataset. Performance levels were lower on the PhysioNet dataset. These results indicate that a viable task recognition system is achievable using pairwise synchronization measures evaluated at the proper task specific lags.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofComputers in Biology and Medicineen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectEEGen_US
dc.subjectBrain connectivityen_US
dc.subjectSynchronization measuresen_US
dc.subjectCognitive task recognitionen_US
dc.subjectMutual informationen_US
dc.subjectPhase locking valueen_US
dc.subjectCross correlationen_US
dc.subjectNonlinear interdependencyen_US
dc.titleEvaluation of synchronization measures for capturing the lagged synchronization between EEG channels: A cognitive task recognition approachen_US
dc.typeArticleen_US
dc.institutionauthorOlcay, Bilal Orkan-
dc.institutionauthorKaraçalı, Bilge-
dc.departmentİzmir Institute of Technology. Electrical and Electronics Engineeringen_US
dc.identifier.volume114en_US
dc.identifier.wosWOS:000495520100012en_US
dc.identifier.scopus2-s2.0-85072511939en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1016/j.compbiomed.2019.103441-
dc.identifier.pmid31561099en_US
dc.relation.doi10.1016/j.compbiomed.2019.103441en_US
dc.coverage.doi10.1016/j.compbiomed.2019.103441en_US
local.message.claim2023-01-27T11:49:33.827+0300|||rp02429|||submit_approve|||dc_contributor_author|||None*
dc.identifier.wosqualityQ1-
dc.identifier.scopusqualityQ2-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.dept01.01. Units Affiliated to the Rectorate-
crisitem.author.dept03.05. Department of Electrical and Electronics Engineering-
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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