Statistical comparison of three analysis methods of fBm sequences

Abstract

Mandelbrot and Van Ness' fructionul Browniun motion (fBm) has been considered a suitable model to describe the long-range correlations exhibited by a wide variety of physiological signals, such as the heart rate. The fBm is a temporal fractal whose properties of self-affinity and infinite inter-dependency of its increments are characterized by a parameter H , referred to as the Hurst exponent. This parameter is quite useful in analysing biomedical signals and determining certain pathologies or physiological states these signals may exhibit. Over the yews, several algorithms for the computation of H have been published. In this study we compme the performance of the well-known Higuchi's method, with two other relatively recent ones. DePetrillo's and Chang's methods. The results reveal that the last one seems to he the most accurate in analysing these sequences.