Multifractality in human heartbeat dynamics

@article{Ivanov1999MultifractalityIH,
  title={Multifractality in human heartbeat dynamics},
  author={Plamen Ch. Ivanov and Luis A. Nunes Amaral and Ary L. Goldberger and Shlomo Havlin and Michael Rosenblum and Zbigniew R. Struzik and Harry Eugene Stanley},
  journal={Nature},
  year={1999},
  volume={399},
  pages={461-465}
}
There is evidence that physiological signals under healthy conditions may have a fractal temporal structure. Here we investigate the possibility that time series generated by certain physiological control systems may be members of a special class of complex processes, termed multifractal, which require a large number of exponents to characterize their scaling properties. We report onevidence for multifractality in a biological dynamical system, the healthy human heartbeat, and show that the… 
Discrimination by multifractal spectral estimation of human heartbeat interval dynamics
TLDR
The characteristic multifractal spectral pattern in heart transplant recipients or chronic heart disease highlights the importance of neuroautonomic control mechanisms regulating the fractal dynamics of the cardiac rhythm.
Self-affine fractal variability of human heartbeat interval dynamics in health and disease
TLDR
The continuous multifractal large deviation spectrum uncovers the nonlinear fractal properties in the dynamics of heart rate and presents a useful diagnostic framework for discrimination and classification of patients with cardiac disease, e.g., congestive heart failure.
Fractal and Multifractal Approaches in Physiology
TLDR
The degree to which concepts developed in statistical physics can be usefully applied to physiological signals is explored and the findings of fractal and multifractal properties in the human heartbeat are discussed and how they change with disease.
Multiscale analysis of heart rate variability
TLDR
By analyzing a number of heart rate variability data, it is shown that the method can accurately distinguish between healthy subjects and patients with congestive heart failure and suggests that the dimension of the dynamics of the cardiovascular system is lower under the healthy than under diseased conditions.
New computational approaches to the analysis of interbeat intervals in human subjects
TLDR
New computational approaches - based on new theoretical concepts - for analyzing physiological time series are described and it is shown that the application of these methods could potentially lead to a novel diagnostic tool for distinguishing healthy individuals from those with congestive heart failure.
Long-Range Dependence in Heartbeat Dynamics
Physiologic signals are generated b complex self-regulating systems that process inputs with a broad range of characteristics [1,2,3]. Man physiological time series are extremely inhomogeneous and
Scaling Behaviour and Memory in Heart Rate of Healthy Human
We investigate a set of complex heart rate time series from healthy human in different behaviour states with the detrended fluctuation analysis and diffusion entropy (DE) method. It is proposed that
Multifractal mass exponent spectrum of complex physiological time series
TLDR
A new measure to characterize multifractality, the mass exponent spectrum curvature, which can disclose the complexity of fractal structure from total bending degree of the spectrum and can be better to discriminate cohorts under different physiological and pathological conditions.
Scale invariance in the nonstationarity of human heart rate.
TLDR
It is found that the lengths of segments with different local mean heart rates follow a power-law distribution and it is shown that this scale-invariant structure is not a simple consequence of the long-range correlations present in the data.
...
...

References

SHOWING 1-10 OF 37 REFERENCES
Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis
TLDR
A new approach is introduced, based on the wavelet transform and an analytic signal approach, which can characterize non-stationary behaviour and elucidate the phase interactions between the different frequency components of the signal.
Decrease of cardiac chaos in congestive heart failure
TLDR
Electrocardiograms from a group of healthy subjects and those with severe congestive heart failure suggest that cardiac chaos is prevalent in healthy heart, and a decrease in such chaos may be indicative of CHF.
Predictability of normal heart rhythms and deterministic chaos.
TLDR
The evidence for a small amount of nonlinear dynamical behavior together with the short-term predictability suggest that there is an element of deterministic chaos in normal heart rhythms, although it is not strong or persistent.
Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series.
TLDR
A new method--detrended fluctuation analysis (DFA)--for quantifying this correlation property in non-stationary physiological time series is described and application of this technique shows evidence for a crossover phenomenon associated with a change in short and long-range scaling exponents.
Lack of Evidence for Low‐Dimensional Chaos in Heart Rate Variability
TLDR
Nonlinear Dynamics in Heart Rate finds that the variability observed in the normal heart rate may be due to chaos, but this question has not been settled.
Nonlinear control of heart rate variability in human infants.
TLDR
The acquisition of nonlinear heart rate dynamics and possible chaos in developing human infants and its loss in brain death and with the administration of atropine is demonstrated and it is suggested that nonlinearity may provide additional power in characterizing physiological states.
Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control.
TLDR
It is shown that sympathetic and parasympathetic nervous activity make frequency-specific contributions to the heart rate power spectrum, and that renin-angiotensin system activity strongly modulates the amplitude of the spectral peak located at 0.04 hertz.
The Multifractal Formalism Revisited with Wavelets
TLDR
It is shown that this method provides a natural generalization of the classical box-counting techniques to fractal functions (the wavelets actually play the role of “generalized boxes”).
I Fractals and multifractals: the interplay of Physics and Geometry
In recent years, a wide range of complex structures of interest to scientists, engineers, and physicans have been quantitatively characterized using the idea of a fractal dimension: a dimension that
...
...