Spectral analysis of internal carotid arterial Doppler signals using FFT, AR, MA, and ARMA methods.
In this study, Doppler signals recorded from internal carotid artery of 45 subjects were processed by PC-computer using classical (fast Fourier transform) and model-based (autoregressive, moving average, autoregressive moving average (ARMA) methods) methods. Power spectral density estimates of internal carotid arterial Doppler signals were obtained using these spectral analysis methods. The variations in the shape of the Doppler power spectra as a function of time were presented in the form of sonograms in order to determine the degree of internal carotid artery stenosis. These Doppler power spectra and sonograms were then used to compare the applied methods in terms of their frequency resolution and the impact on determining stenosis in internal carotid arteries. Based on the results, performance characteristics of the autoregressive and ARMA methods were found extremely valuable for spectral analysis of internal carotid arterial Doppler signals obtained from healthy subjects and unhealthy subjects having artery stenosis.
Ubeyli
Elif Derya
ED
Department of Electronics and Computer Education, Faculty of Technical Education, Gazi University, 06500 Teknikokullar, Ankara, Turkey.
Güler
Inan
I
D000293:Adolescent; D000328:Adult; D001783:Blood Flow Velocity / Q000502:physiology; D002343:Carotid Artery, Internal / Q000000981:diagnostic imaging* / Q000503:physiopathology; D016893:Carotid Stenosis / Q000000981:diagnostic imaging / Q000503:physiopathology; D003198:Computer Simulation; D005260:Female; D005583:Fourier Analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D012815:Signal Processing, Computer-Assisted; D018608:Ultrasonography, Doppler / Q000379:methods*; D018084:Ultrasonography, Interventional