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Identification of dynamical noise levels in chaotic systems and application to cardiac dynamics analysis

It is by now widely appreciated that normal heart rhythms show features of deterministic chaos, and it is also corrupted by a great deal of physiological noises from surroundings as the inputs to the chaotic system. We study the effects of measurement and dynamical noises on low-dimensional chaotic systems, and present a numerical algorithm for estimating to what extent heart rhythm is corrupted by dynamical noises. Further analysis shows that adding increasing amounts of dynamical noise increasingly develops the complexity of chaotic dynamics. The method need not fully reconstruct an attractor, thus it is robust to measurement noises. Finally, the ECG of 53 subjects falling into three groups were used to test the algorithm. From the measured R-R intervals, a time series of 1000 first order difference points was used to estimate dynamical noise levels. We found that the estimated dynamical noise levels were correlated to the different classes of ECG.