Epileptik EEG İşaretlerinin Sınıflandırılması İçin Yeni Bir Öznitelik Çıkarım Yöntemi

Year 2018, Volume: 22 Issue: Special, 529 - 535, 05.10.2018

Ramazan Tekin , Yılmaz Kaya

Abstract

Epilepsi en sık karşılaşılan nörolojik hastalıklardan biri olup beyinde bir grup nöronun anormal aktivitesi sonucu oluşmaktadır. Epilepsi genellikle elektroansefalografi (EEG) sinyalleri kullanılarak teşhis edilmektedir. Bu sebeple, EEG işaretlerinden etkin özniteliklerin çıkarılması doğru sınıflandırma için önemli bir basamaktır. Bu çalışmada epileptik EEG işaretlerinden kararlı öznitelikler çıkaracak motif algoritması isimli yeni bir yaklaşım önerilmiştir. Bu yaklaşım, EEG işaretlerinde belirli büyüklükteki bir pencere içine giren değerlerin birbirleri ile olan büyüklük/küçüklük ilişkisine bağımlıdır. Pencere içindeki değerlerin birbirlerine göre oluşturdukları görünüm bir motif olarak ele alınmaktadır. İşaret üzerindeki bu motiflerin frekansları öznitelik vektörü olarak kullanılmıştır. Motif sayısı sinyal üzerinde tanımlanan pencere boyutuna bağlıdır. Motif öznitelikleri elde edildikten sonra sınıflama aşamasında RF, YSA, SVM gibi farklı sınıflandırma algoritmaları kullanılmıştır.  Önerilen yöntemin başarısını test etmek için farklı durumlarda (nöbet öncesi, nöbet sonrası, gözler açık ve gözler kapalı vb.) kayıt altına alınmış EEG işaretlerinin birleşimlerinden elde edilen setler kullanılmış ve yüksek sınıflandırma başarıları elde edilmiştir.

Keywords

Elektroansefalografi, Epilepsi; Motif öznitelikler; Öznitelik çıkarımı

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