Application of non-Gaussian statistics to heart rate variability analysis

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Time series analysis methods to characterize deviation from Gaussian distribution (non-Gaussian properties) were developed. To characterize asymmetric properties in observed time series, we proposed positive- or negative-directional non-Gaussian statistics. Using this method, it was demonstrated that the asymmetric properties of heart rate variability depend on aging. In addition, to characterize a wide variety of symmetric non-Gaussian distributions with fat tails, we introduced a multiplicative stochastic process in which an observed time series is assumed to be described by the multiplication of Gaussian and amplitude random variables. Based on this framework, we proposed an analysis method using log-amplitude cumulants. As an application of this method, we showed the relation between non-Gaussian shapes of heart rate variability and mortality in heart failure patients.