Kapsül Ağları Kullanılarak EEG Sinyallerinin Sınıflandırılması

Year 2020, Volume: 32 Issue: 1, 203 - 209, 03.03.2020

Suat Toraman

https://doi.org/10.35234/fumbd.661955

Cited By: 3

Abstract

Epilespi dünyadaki her yüz kişiden birinin sıkıntı çektiği en yaygın nörolojik hastalıklardan biridir. Gerçekleşecek bir nöbetin önceden tahmin edilebilmesi, epilepsi hastalarının yaşam kalitesinin artırılmasında önemli bir rol oynayacaktır. Ayrıca, etkili bir nöbet tahmin sistemi, hastalığın daha kontrol edilebilir olmasını sağlayacaktır. Bu çalışmada, Elektroansefalogram (EEG) sinyallerindeki interiktal ve preiktal beyin aktivitelerini ayırt etmek için bir yöntem önerilmiştir. Önerilen yöntemde, yeni bir sinir ağı modeli olan kapsül ağları kullanılmıştır. Preiktal aktivite, nöbet başlangıcından 30dk ileride seçilmiştir. Preiktal ve interiktal kısımlar kayan pencere ile segmentlere ayrılmış ve her segmentin spektrogram görüntüleri elde edilmiştir. Spektrogram görüntüleri, kapsül ağları kullanılarak C3-P3 için ortalama %94.05 doğruluk ile sınıflandırılmıştır. Bu çalışma ile kapsül ağlarının preiktal/interiktal sınıflandırma başarımı incelenmiştir. Elde edilen sonuçlar, kapsül ağlarının epilepsinin tahmini için umut verici bir yöntem olduğunu göstermektedir.

Keywords

EEG, Epilepsi, Kapsül Ağları, Preiktal-interiktal tanıma

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