Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6704
Title: Feature extraction by autoregressive spectral analysis using maximum likelihood estimation: internal carotid arterial Doppler signals
Authors: Übeyli, Elif Derya
Keywords: Doppler signal
spectral analysis
power spectral density
sonogram
internal carotid artery
Issue Date: 2008
Publisher: Wiley-Blackwell
Abstract: In this study, Doppler signals recorded from the internal carotid artery (ICA) of 97 subjects were processed by personal computer using classical and model-based methods. Fast Fourier transform (classical method) and autoregressive (model-based method) methods were selected for processing the ICA Doppler signals. The parameters in the autoregressive method were found by using maximum likelihood estimation. The Doppler power spectra of the ICA Doppler signals were obtained by using these spectral analysis techniques. The variations in the shape of the Doppler spectra as a function of time were presented in the form of sonograms in order to obtain medical information. These Doppler spectra and sonograms were then used to compare the applied methods in terms of their frequency resolution and the effects in determination of stenosis and occlusion in the ICA. Reliable information on haemodynamic alterations in the ICA can be obtained by evaluation of these sonograms.
URI: https://doi.org/10.1111/j.1468-0394.2008.00448.x
https://hdl.handle.net/20.500.11851/6704
ISSN: 0266-4720
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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