Classification of imaginary movements in ECoG with a hybrid approach based on multi-dimensional Hilbert-SVM solution

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dc.contributor.authorDemirer, R. Murat
dc.contributor.authorOzerdem, Mehmet Sirac
dc.contributor.authorBayrak, Coskun
dc.date.accessioned2024-04-24T16:15:10Z
dc.date.available2024-04-24T16:15:10Z
dc.date.issued2009
dc.departmentDicle Üniversitesien_US
dc.description.abstractThe study presented in this paper shows that electrocorticographic (ECoG) signals can be classified for making use of a human brain-computer interface (BCI) field. The results show that certain invariant phase transition features can be reliably used to classify two types of imagined movements accurately. Those are the left small-finger and tongue movements. Our approach consists of two main parts: channel selection based on Tsallis entropy in Hilbert domain and the nonlinear classification of motor imagery with support vector machines (SVMs). The new approach, based on Hilbert and statistical/entropy measurements, were combined with SVMs based on admissible kernels for classification purposes. The classification accuracy rates were 95% (264/278) and 73% (73/100) for training and testing sets, respectively. The results support the use of classification methods for ECoG-based BCIs. Published by Elsevier B.V.en_US
dc.identifier.doi10.1016/j.jneumeth.2008.11.011
dc.identifier.endpage218en_US
dc.identifier.issn0165-0270
dc.identifier.issn1872-678X
dc.identifier.issue1en_US
dc.identifier.pmid19084556
dc.identifier.scopus2-s2.0-59449083403
dc.identifier.scopusqualityQ2
dc.identifier.startpage214en_US
dc.identifier.urihttps://doi.org/10.1016/j.jneumeth.2008.11.011
dc.identifier.urihttps://hdl.handle.net/11468/15684
dc.identifier.volume178en_US
dc.identifier.wosWOS:000264013000029
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofJournal of Neuroscience Methods
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBrain Computer Interfaceen_US
dc.subjectEcogen_US
dc.subjectClassificationen_US
dc.subjectMulti-Dimensional Hilbert Transformationen_US
dc.subjectSvmen_US
dc.titleClassification of imaginary movements in ECoG with a hybrid approach based on multi-dimensional Hilbert-SVM solutionen_US
dc.titleClassification of imaginary movements in ECoG with a hybrid approach based on multi-dimensional Hilbert-SVM solution
dc.typeArticleen_US

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