Impact of hybrid neural network on the early diagnosis of diabetic retinopathy disease from video-oculography signals

In this study, we introduce two hybrid artificial neural network models with particle swarm optimization algorithm to diagnose diabetic retinopathy based on the Video-Oculography signals. The hybrid models use Discrete Wavelet Transform and Hilbert-Huang Transform separately to extract features from the signals. The classification performance of both models is analyzed comparatively. We show that the model based on Hilbert-Huang Transform exhibits better classification performance than the model based on the Discrete Wavelet Transform.