The RR series extracted from human electrocardiogram signal (ECG) is
considered as a fractal stochastic process. The manifestation of long-range
dependencies is the presence of power laws in scale dependent process
characteristics. Exponents of these laws: β - describing power spectrum
decay, α - responsible for decay of detrended fluctuations or H
related to, so-called, roughness of a signal, are known to differentiate hearts
of healthy people from hearts with congestive heart failure. There is a strong
expectation that resolution spectrum of exponents, so-called, local exponents
in place of global exponents allows to study differences between hearts in
details. The arguments are given that local exponents obtained in multifractal
analysis by the two methods: wavelet transform modulus maxima (WTMM) and
multifractal detrended fluctuation analysis (MDFA), allow to recognize the
following four stages of the heart: healthy and young, healthy and advance in
years, subjects with left ventricle systolic dysfunction (NYHA I--III class)
and characterized by severe congestive heart failure (NYHA III-IV class).Comment: 24 page