Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6199
Title: Adaptive neuro-fuzzy inference system for analysis of Doppler signals
Authors: Übeyli, Elif Derya
Keywords: adaptive neuro-fuzzy inference system (ANFIS)
fuzzy logic
wavelet transform
doppler signal
ophthalmic artery stenosis
Issue Date: 2006
Publisher: IEEE
Source: 28th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society -- AUG 30-SEP 03, 2006 -- New York, NY
Abstract: 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 had suffered from ophthalmic artery stenosis and the rest of them had been 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 (total classification accuracy was 97.59%) and the results confirmed that the proposed ANFIS classifier has potential in detecting the ophthalmic artery stenosis.
URI: https://hdl.handle.net/20.500.11851/6199
ISBN: 978-1-4244-0032-4
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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