Epileptic seizureprediction based on Hilbert Huang Transform and Artificial Neural Networks

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dc.authorscopusid57198276954
dc.authorscopusid43262125900
dc.contributor.authorÖzdemir, Nilufer
dc.contributor.authorYildirim, Esen
dc.date.accessioned2024-09-19T15:41:14Z
dc.date.available2024-09-19T15:41:14Z
dc.date.issued2012
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description2012 20th Signal Processing and Communications Applications Conference, SIU 2012 -- 18 April 2012 through 20 April 2012 -- Fethiye, Mugla -- 90786en_US
dc.description.abstractFor a patient diagnosed with epilepsy, a neurological disorder that affects the patient only during a seizure, and the following short duration for some cases, it is important to predict a seizure before it happens. EEG signal processing plays an important role in detection and prediction of epileptic seizures. The aim of this study is to develop a patient specific seizure prediction method based on Hilbert-Huang Transform. In this method EEG signals are decomposed into Intrinsic Mode Functions and first six IMFs are used to obtain features for classification of preictal and interictal recordings employing Artificial Neural Networks. Proposed method was tested on Freiburg iEEG database. A total of 58 hours of preictal data, prior to 87 seizures, and 504 hours of interictal data were examined. Algorithm resulted in 93.1% sensitivity (81 of 87 seizures) and 0.71 FPs/h using 30 seconds EEG segment with 50% overlap. © 2012 IEEE.en_US
dc.identifier.doi10.1109/SIU.2012.6204748
dc.identifier.isbn978-146730056-8
dc.identifier.scopus2-s2.0-84863451991en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/SIU.2012.6204748
dc.identifier.urihttps://hdl.handle.net/20.500.12483/14104
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.relation.ispartof2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectForecastingen_US
dc.subjectNeural networksen_US
dc.subjectPatient monitoringen_US
dc.subjectSignal processingen_US
dc.subjectEEG signal processingen_US
dc.subjectEEG signalsen_US
dc.subjectEpileptic seizuresen_US
dc.subjectHilbert Huang transformsen_US
dc.subjectIntrinsic Mode functionsen_US
dc.subjectNeurological disordersen_US
dc.subjectPatient specificen_US
dc.subjectSeizure predictionen_US
dc.subjectShort durationsen_US
dc.subjectMathematical transformationsen_US
dc.titleEpileptic seizureprediction based on Hilbert Huang Transform and Artificial Neural Networksen_US
dc.title.alternativeHilbert Huang Transform ve Yapay Si?ni?r A?lari i?le epi?lepti?k nöbet tahmi?ni?en_US
dc.typeConference Objecten_US

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