Show simple item record

dc.contributor.authorFernández-Blanco, Enrique
dc.contributor.authorRivero, Daniel
dc.contributor.authorRabuñal, Juan R.
dc.contributor.authorDorado, Julián
dc.contributor.authorPazos, A.
dc.contributor.authorMunteanu, Cristian-Robert
dc.date.accessioned2021-03-24T15:46:09Z
dc.date.available2021-03-24T15:46:09Z
dc.date.issued2012-08-15
dc.identifier.citationFernandez-Blanco, E., Rivero, D., Rabunal, J., Dorado, J., Pazos, A., & Munteanu, C. R. (2012). Automatic seizure detection based on star graph topological indices. Journal of neuroscience methods, 209(2), 410-419.es_ES
dc.identifier.issn0165-0270
dc.identifier.urihttp://hdl.handle.net/2183/27587
dc.description.abstract[Abstract] The recognition of seizures is very important for the diagnosis of patients with epilepsy. The seizure is a process of rhythmic discharge in brain and occurs rarely and unpredictably. This behavior generates a need of an automatic detection of seizures by using the signals of long-term electroencephalography (EEG) recordings. Due to the non-stationary character of EEG signals, the conventional methods of frequency analysis are not the best alternative to obtain good results in diagnostic purpose. The present work proposes a method of EEG signal analysis based on star graph topological indices (SGTIs) for the first time. The signal information, such as amplitude and time occurrence, is codified into invariant SGTIs which are the basis for the classification models that can discriminate the epileptic EEG records from the non-epileptic ones. The method with SGTIs and the simplest linear discriminant methods provide similar results to those previously published, which are based on the time-frequency analysis and artificial neural networks. Thus, this work proposes a simpler and faster alternative for automatic detection of seizures from the EEG recordings.es_ES
dc.description.sponsorshipXunta de Galicia; 2007/127es_ES
dc.description.sponsorshipXunta de Galicia; 2007/144es_ES
dc.description.sponsorshipInstituto de Salud Carlos III; PIO52048es_ES
dc.description.sponsorshipInstituto de Salud Carlos III; RD07/0067/0005es_ES
dc.description.sponsorshipMinisterio de Ciencia e Innovación; TIN2009—07707.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.urihttps://doi.org/10.1016/j.jneumeth.2012.07.004es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectAutomatic signal processinges_ES
dc.subjectEpilepsy seizure detectiones_ES
dc.subjectEEG signales_ES
dc.subjectStar graphses_ES
dc.subjectLinear discriminant analysises_ES
dc.titleAutomatic Seizure Detection Based on Star Graph Topological Indiceses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleJournal of Neuroscience Methodses_ES
UDC.issue209es_ES
UDC.startPage410es_ES
UDC.endPage419es_ES
dc.identifier.doi10.1016/j.jneumeth.2012.07.004


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record