Elif Derya UBEYL İ , İ nan GÜLER APPLICATION OF ADAPTIVE NEURO - FUZZY INFERENCE SYSTEM FOR ANALYSIS OF OPHTHALMIC ARTERIAL DOPPLER SIGNALS USING FEATURE EXTRACTION

In this study, a new approach based on adaptive neuro-fuzzy inference system (ANFIS) was presented for detection of ophthalmic artery stenosis. Decision making was performed in two stages: feature extraction using the wavelet transform (WT) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. The ophthalmic arterial Doppler signals were recorded from 128 subjects that 62 of them suffered from ophthalmic artery stenosis and the rest of them were healthy subjects. Some conclusions concerning the impacts of features on the detection of ophthalmic artery stenosis were obtained through analysis of the ANFIS. The performance of the ANFIS classifier was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS classifier has potential in detecting the ophthalmic artery stenosis.