Nonlinear analysis of Heart Rate Variability signal for the characterization of Cardiac Heart Failure patients

The purpose of this work is to characterize the heart rate variability (HRV) of patients affected by congestive heart failure (CHF) and to find out the main difference between this pathological condition and the physiological state. Parameters adopted in this work are: the detrended fluctuation analysis (DFA) and the Higuchi exponent to assess long correlations and self-similarity; the regularity estimators, approximate entropy (ApEn) and sample entropy (SampEn) and the multiscale entropy (MSE). Furthermore we proposed a new regularity index, the Gaussian entropy (GaussEn) which is a modification of the previous ApEn and SampEn. The results show the proposed parameters do an effective separation of physiological and pathological subject conditions. These results are part of a study evaluating the nonlinear index prognostic value toward cardiac death