Fokal ve Fokal Olmayan EEG Sinyallerinin Sınıflandırılması

Year 2021, Volume: 17 Issue: 1, 20 - 29, 30.06.2021

Bayram Karaman , Ayşegül Güven

Abstract

Epilepsi beyinde bulunan nöronlarda ani ve kontrolsüz boşalmalar sonucu oluşan nörofizyolojik bir hastalıktır. Dünya üzerinde birçok insan epilepsi hastalığından muzdariptir. Fokal (F) ve Fokal olmayan (NF) bölgelerin Elektroensefalogram (EEG) sinyalleri üzerinden otomatik olarak sınıflandırılması epilepsi hastalığının teşhisinde önemli bir yere sahiptir. Önerilen çalışmada F ve NF EEG sinyallerinin dalgacık katsayıları için Ayrık Dalgacık Dönüşümü kullanılmıştır. Bu katsayılardan Shannon Entropi, Log Enerji Entropi, Aritmetik Ortalama ve Medyan olarak dört özellik çıkarılmıştır. Bu özellikler WEKA (bilgi analizi için wikato ortamı) programında yer alan Lojistik Regresyon (LR) ve Destek Vektör Makineleri (SVM) algoritmaları ile sınıflandırılmıştır. Yapılan bu sınıflandırmalar sonucunda LR ve SVM sırasıyla %81 ve %83 sınıflandırma doğruluğu elde edilmiştir.

Keywords

Epilepsi, Elektroensefalogram, Lojistik Regresyon, Destek Vektör Makineleri

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