Order determination in autoregressive modeling of diastolic heart sounds.

Previous studies demonstrated that spectral analysis of diastolic heart sounds may provide valuable information for the detection of coronary artery disease. Although parametric modeling methods were successfully used to achieve this goal, and showed considerable performance, the accuracy and precision of the analysis is strongly dependent on the model order selected. In order to investigate the effects of model order selection on the analysis, diastolic heart sound recorded from both normal and diseased patients were analyzed using the AR modeling, which is computationally the most efficient parametric spectral analysis method.

Application of autoregressive and Fast Fourier Transform spectral analysis to tricuspid and mitral valve stenosis.

Tricuspid and mitral valve flow area was determined from an apical four-chamber view. Doppler signals were recorded from normal subjects and patients with tricuspid and mitral valve stenosis by using a pulsed Doppler unit. The location of sample volume was chosen at the ventricular side of the valve orifice and within the right ventricular tract.

Comparison of FFT- and AR-based sonogram outputs of 20 MHz pulsed Doppler data in real time.

Real time sonogram outputs of autoregressive (AR) and Fast Fourier Transform (FFT) spectral analysis of 20 MHz pulsed ultrasonic Doppler blood flowmeter are presented. Data obtained from coronary, renal, iliac, digital and mesenteric arteries were processed using AR- and FFT-based spectral analysis techniques and interpretable sonograms were constructed. In comparison with the FFT-based sonogram outputs.

Autoregressive-based sonogram outputs of 20 MHz pulsed Doppler data.

The sonogram outputs of autoregressive (AR) based spectral analysis of a 20 MHz pulsed ultrasonic Doppler blood flowmeter are presented. The data obtained from coronary and iliac arteries were processed using AR-based spectral analysis technique, and then the interpretable sonograms by the surgeons were constructed. When the sonogram outputs were compared to other sonograms which were analysed using the other techniques such as fast Fourier transform (FFT), it was observed that AR-based sonograms for 20 MHz pulsed Doppler data have provided better results.

Application of autoregressive analysis to 20 MHz pulsed Doppler data in real time.

The real time application of autoregressive (AR) spectral analysis to a 20-MHz pulsed Doppler blood flowmeter is presented. The system consists of a TMS 320C25 digital signal processor with a 80286 based PC/AT microcomputer and associated interfacing circuitry. The AR method was used for in vivo spectral analysis of the signals obtained from a 20-MHz pulsed Doppler flowmeter in real time.