Noninvasive diagnosis of atherosclerosis by using empirical mode decom- position, singular spectral analysis, and support vector machines

In recent years, the use of Doppler ultrasound sonography for the diagnosis of atherosclerosis has increased. However, parameters provided by the commercially available Doppler ultrasound units are inadequate to compete with the gold standard method, catheter angiography. Therefore, developing a new method based on Doppler ultrasound sonography remains a hot topic among researchers. In this study, a diagnostic method based on empirical mode decomposition, singular spectral analysis, and support vector machines is proposed. The nonlinear and non-stationary nature of the Doppler ultrasound sonogram is utilized in the analysis. Empirical mode decomposition is a suitable tool for such signals. Singular spectral analysis is used to construct the classifications feature set. Finally, support vector machine classification is applied. When compared with clinical findings and similar methods, the proposed method provides excellent results.