In our study, the nonlinear dynamics of initial valve Doppler signals from 32 healthy and 28 patients with initial valve stenosis was evaluated using by the computation of Lyapunov exponents, correlation dimension values and surrogate data analysis Two chaotic features are compared for healthy and patient subjects It was found that the hugest Lyapunov exponent and correlation dimension values derived from patient subjects were larger than that of healthy subjects (rho < 0 005) Surrogate data analysis was performed to determine the chaotic dynamics of Doppler signals It was observed that the original and surrogate data have similar spectral features Receiver, operating characteristic (ROC) curves were used to evaluate the nonlinearity character Area Under the curve (AUC) values were obtained as 0 99 and 0 978 for the largest Lyapunov exponent and correlation dimension, values, respectively According to these results. Doppler signals have a nonlinear dynamic property and the largest Lyapunov exponent Correlation dimension features can be used to detect the change in blood flow velocity of patients with mitral valve stenosis
In our study, the nonlinear dynamics of mitral valve Doppler signals from 32 healthy and 28 patients with
mitral valve stenosis was evaluated using by the computation of Lyapunov exponents, correlation dimension
values and surrogate data analysis. Two chaotic features are compared for healthy and patient subjects. It
was found that the largest Lyapunov exponent and correlation dimension values derived from patient subjects
were larger than that of healthy subjects (ρ <0.005). Surrogate data analysis was performed to determine
the chaotic dynamics of Doppler signals. It was observed that the original and surrogate data have similar
spectral features. Receiver operating characteristic (ROC) curves were used to evaluate the nonlinearity
character Area Under the curve (AUC) values were obtained as 0.99 and 0.978 for the largest Lyapunov
exponent and correlation dimension values, respectively. According to these results, Doppler signals have a
nonlinear dynamic property and the largest Lyapunov exponent. Correlation dimension features can be used
to detect the change in blood flow velocity of patients with mitral valve stenosis.
