arXiv subjects

Aleksandra Dudkowska

Publications and source records attributed to Aleksandra Dudkowska.

3 recordsLinked to original sources

arXiv2007

Multifractal analysis of normal RR heart-interbeat signals in power spectra ranges

Power spectral density is an accepted measure of heart rate variability. Two estimators of multifractal properties: Wavelet Transform Modulus Maxima and Multifractal Detrended Fluctuation Analysis are used to investigate multifractal properties for the three strongly physiologically grounded components of power spectra: low frequency (LF), very low frequency (VLF) and ultra low frequency (ULV). Circadian rhythm changes are examined by discrimination of daily activity from nocturnal rest. Investigations consider normal sinus rhythms of healthy 39 subjects which are grouped in two sets: 5-hour wake series and 5-hour sleep series. Qualitative arguments are provided to conjecture the presence of stochastic persistence in LF range, loss of heart rate variability during night in VLF range and its increase in ULF.

q-bio.QM↗

arXiv2006

Influence of stochastic delays in Seidel-Herzel model of human cardiorespiratory system

Experiments that discuss influence of noise to H. Seidel and H. Herzel dynamics model of human cardiovascular system are presented. Noise is introduced by considering stochastic delays in response to the sympathetic system. It appears that in the presence of the noise 10 s heart rate oscillations connected with Mayer waves are preserved. Moreover the heart rate becomes approximately normally distributed (even in unstable phase of original Seidel Herzel model), similarly like the real RR intervals data.

q-bio.TO↗

arXiv2005

Long-range dependencies in heart rate signals- revisited

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).

q-bio.TO↗