Göz Özelliklerinin LSTM-PSO Modeli kullanılarak Otizm Sınıflandırılması

Yıl 2023, Cilt: 14 Sayı: 4, 563 - 570, 31.12.2023

Dilber Çetintaş Taner Tuncer

https://doi.org/10.24012/dumf.1327654

Öz

Otizm birçok biyobelirteci olan karmaşık bir rahatsızlıktır. Bu karmaşık rahatsızlığı tanımlamak ve ayırtedebilmek birden fazla biyolojik özelliği kullanarak mümkün olabilmektedir. Bu özelliklerden biri de göz hareketleridir. Çalışma kullanıcılara özgü gözbebeği boyutu, göz pozisyonları(X-Y koordinatları), ilgi alanının noktaları, iris yarıçapı parametrelerinden oluşan dizileri kullanarak otizm spektrum bozukluğu olan (OSB) ve otizm spektrum bozukluğu olmayan (TS) bireyleri LSTM ağı ile otomatik olarak sınıflandırmayı amaçlamaktadır. Bu doğrultuda ilk adım olarak herbir hareketin tüm parametreleri ayrı bir dizi olarak alınır. Alınan diziler ikinci basamakta LSTM ağında işlenir. İşleme aşamasında pencere boyutunun doğru şeçilmesi sonucu etkileyen en önemli faktörlerden biridir. Bu doğrultuda modelde pencere boyutunun optimum seçilebilmesi için PSO (Parçacık Sürü Optimizasyonu) algoritması kullanılır. LSTM-PSO hibrit modeli kullanılarak iki senaryo gerçekleştirilir. Bu senaryolardan biri tüm özellikleri içerirken senaryo 2’de sadece gözbebeği boyutu ve ilgi alanı özellikleri mevcuttur ve DVM (Destek Vektör Makinesi) sınıflandırıcısı ile başarı oranı senaryo 2’de %98,64 maximum olarak ölçülür. Sonuç göz izleme verileri kullanılarak otizmin LSTM ile sınıflandırılmasının mümkün olduğunu ve bu yöntemin otizm tanısı ve tedavisi için potansiyel olarak faydalı olabileceğini göstermektedir.

Anahtar Kelimeler

Göz hareketleri, LSTM, PSO, Pencere Boyutu

Kaynakça

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