Nonlinear dynamic approach in the analysis of cardiovascular variability signals in normal and pathological subjects

We study the complex, long-term dynamics underlying the Heart Rate variability (HRV) signal through the chaotic deterministic approach. We calculate the geometric fractal dimension of the system space state, the Entropy, the maximum positive λ1 Lyapunov Exponent and the self similarity Hurst exponent in HRV. These parameters estimate the properties of a nonlinear dynamic system. Data were also submitted to a determinism test. Series of about 20,000 R-R intervals were selected in 24h Holter recordings 9 Normal subjects, 6 hypertensive, 11 severe heart failure and 7 orthotopic transplanted in day and night epochs. Correlation dimension (D2), Entropy (K) and H self similar parameter show a significant decrease passing from normal to pathological subjects. The trend of various and different parameters suggests nonlinear dynamic in the generation mechanism of HRV signal. Interpretation of results seems consistent with a complex cardiovascular pathophysiology that shows, in the long-term regulation, nonlinear properties.