Abstract
The dynamic characteristics of heart rate variability (HRV) are of great significance to the pathological analysis of cardiovascular disease. The paper presents a nonlinear analysis of heart rate data from different populations based on the Chaos and Fractal Theory. Firstly, the qualitative analysis on the long-range dependence and chaotic characteristics of heart rate data is made through power spectrum and two-dimensional phase diagram. Hurst exponents are then calculated by R/S Analysis (Rescaled Range Analysis), testifying to the feature of long-range dependence of heart rate data. By phase space reconstruction, we obtain the correlation dimensions and the positive Lyapunov exponents and they verify the dynamic characteristics of heart rate data. Different physiological features are finally discussed by comparing these nonlinear features, which shows the established clinical utility of Chaos Theory in heart rate analysis.
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