The 3 rd European Medical and Biological Engineering Conference November 20 – 25, 2005 EMBEC'05 Prague, Czech Republic IFMBE Proc. 2005 11(1) ISSN: 1727-1983 © 2005 IFMBE ANALYSIS OF LOWER EXTREMITY VENOUS DOPPLER SIGNALS USING SPECTRAL BROADENING INDEX Semra İçer*, Sadık Kara** * Erciyes University, Biomedical Devices Technology Dept. Kayseri, Turkey ** Erciyes University, Department of Electrical Engineering, Kayseri, Turkey ksemra@erciyes.edu.tr Abstract: This study researches the behaviour of spectral broadening index (SBI) obtained from spectra achived using Short-Time Fourier Transform (STFT) analysis compared to that of SBI based on Autoregressive (AR) Modeling of clinical Doppler lower extremity vein signal. Doppler signals from 12 healthy subjects with eight different physiologic situations were analysed. Sonograms acquired from Doppler signals were used to compare the applied methods in terms of their frequency resolution and their effectiveness for the determination of SBI. The AR based sonograms produced narrower spectra compared to STFT sonograms. Besides, the magnitude of the STFT based SBI was larger than that of the AR based SBI. Furthermore, standart deviations and coefficient of variations of STFT and AR based SBIs changed according to each physiologic situation. The results of this research have also shown that despite the qualitative improvement in the individual frequency spectra, there was no quantitative advantage in using the AR approach over the STFT for the determination of SBI morever there was also an additional computational complexity income connections with AR modeling. Introductıon Ultrasonic Doppler flow imaging has become a powerfull tool in clinical applications. The Doppler effect, resulting from interaction of the ultrasonic wave with moving red blood cells, has been extensively used to determine blood flow velocity [1]. By using spectrum analysis techniques, the variations in the shape of the Doppler spectra are presented in the form of sonograms in order to obtain medical information [2-4]. The use of spectrum analysis to display Doppler frequency shift signals provides not only the best means of measuring blood-flow velocity but also information about the presence of disturbed flow [5]. The detection of blood flow is more difficult in veins due to occuring lower frequency shifts. Doppler signals from slow-flowing blood are closer to the noise level and, consequently, largely filtered out by most continuous-wave instruments. This limitation is overcome by transiently enhancing venous flow by the use of augmentation maneuvers [2, 6]. Color Doppler is used for the detection of stenosis, but quantification of its strenght could be done sing an index extracted from the Doppler spectrum such as the spectral broadening index (SBI) [7]. Kaluzynski and Palko (1993) studied the behaviour of SBI and other indices under different conditions for the spectrum analysis of simulated signals and concluded that the instability of the spectral estimates (of simulated data) had only a limited effect on the indices derived from the spectrum. Keeton et al. (1997) also used simulated data and studied the robustness of Fourier-based and AR- based SBI in noise and the behaviour of AR-SBI with model order. They concluded that although AR had better spectral matching characteristics than the FFT approach, there was no significant improvement in the estimation of the SBI by using the AR technique even in the presence of noise [7-9]. A number of spectral estimation methods have recently been developed for Doppler ultrasonic signal processing [10. 11]. Ubeyli and Guler (2004) studied the spectral analysis of ophthalmic arterial Doppler signals using STFT and Wavelet Transform. They demonstrated that despite the qualitative improvement in the individual sonograms, no quantitative advantage in using the WT over the STFT for the determination of spectral broadening index was obtained due to the poorer variance of the wavelet transform-based spectral broadening index and the additional computational requirements of the wavelet transform [12]. The main aim of this paper is that comparison and calculation spectral broadening index through STFT and AR modeling using real clinical Doppler venous signals with different physiologic situations because of select appropriate signal processing method for venous signals and so diagnostic vein disease. Materials and Methods The signals were recorded from left common femoral veins of 12 healthy males (mean age, 23 years; range, 20-27 years) by an expert Radiologist. Before the data were obtained, a color and pulsed Doppler ultrasound examination of the left femoral vein was performed in order to exclude a venous pathology by using a color Doppler Ultrasound unit (Toshiba PowerVision 6000). A linear ultrasound probe of 10