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

Area of Science:

• Biomedical Engineering
• Medical Signal Processing
• Cardiovascular Diagnostics

Background:

• Pulsed Doppler ultrasound is crucial for blood flow measurement.
• Spectral analysis of Doppler signals aids in diagnosing vascular conditions.
• Real-time processing is essential for clinical applications.

Purpose of the Study:

• To present the real-time application of autoregressive (AR) spectral analysis for a 20-MHz pulsed Doppler blood flowmeter.
• To compare the efficacy of AR spectral analysis against Fast Fourier Transform (FFT) spectral analysis for in vivo Doppler signals.
• To evaluate the potential of AR spectral analysis in examining small blood vessels.

Main Methods:

• Implementation of an AR spectral analysis system using a TMS 320C25 digital signal processor and a PC/AT microcomputer.
• Acquisition and real-time processing of in vivo Doppler signals from digital and coronary arteries.
• Comparative analysis of AR and FFT spectral analysis methods on data from normal and stenotic coronary arteries.

Main Results:

• Autoregressive spectral analysis provided superior spectral resolution and accuracy compared to FFT.
• The AR method successfully processed real-time Doppler signals from various arterial locations.
• The system demonstrated effectiveness in analyzing signals from both healthy and diseased (stenotic) coronary arteries.

Conclusions:

• Autoregressive spectral analysis offers significant advantages over FFT for real-time Doppler blood flow signal processing.
• The developed AR system is suitable for the examination of small caliber arteries, including digital, coronary, renal, iliac, and mesenteric vessels.
• This technique has the potential to enhance the non-invasive diagnosis of vascular diseases.