Multifractality in human heartbeat dynamics

@article{Ivanov1999MultifractalityIH,
  title={Multifractality in human heartbeat dynamics},
  author={P. Ivanov and L. Amaral and A. Goldberger and S. Havlin and M. Rosenblum and Z. Struzik and H. 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… Expand

Figures and Topics from this paper

Discrimination by multifractal spectral estimation of human heartbeat interval dynamics
The complexity of the cardiac rhythm is demonstrated to exhibit self-affine multifractal variability. The dynamics of heartbeat interval time series was analyzed by application of the multifractalExpand
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. Expand
From 1/f noise to multifractal cascades in heartbeat dynamics.
TLDR
The degree to which concepts developed in statistical physics can be usefully applied to physiological signals is explored, and very recent work that quantifies multifractal features in these cascades is described, and the discovery that the multifractional structure of healthy dynamics is lost with congestive heart failure is described. Expand
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. Expand
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. Expand
Influence of the loss of time-constants repertoire in pathologic heartbeat dynamics
We present a fractal analysis of diurnal heart interbeat time series from healthy young subjects and patients with congestive heart failure. We describe some differences between these groups by meansExpand
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. Expand
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 andExpand
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 thatExpand
Multifractal mass exponent spectrum of complex physiological time series
Physiological signal belongs to the kind of nonstationary and time-variant ones. Thus, the nonlinear analysis methods may be better to disclose its characteristics and mechanisms. There have beenExpand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 37 REFERENCES
Fractal mechanisms and heart rate dynamics. Long-range correlations and their breakdown with disease.
TLDR
Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as motivating development of novel physiologic models of systems that appear to be heterodynamic rather than homeostatic. Expand
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. Expand
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. Expand
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. Expand
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. Expand
Scale-independent measures and pathologic cardiac dynamics.
TLDR
It is found that scale-independent measures effectively distinguish healthy from pathologic behavior and a new two-variable scale- independent measure that could be clinically useful is proposed. Expand
Multiresolution Wavelet Analysis of Heartbeat Intervals Discriminates Healthy Patients from Those with Cardiac Pathology
TLDR
Every patient in a standard data set is correctly classified as belonging either to the heart-failure or normal group with 100% accuracy, thereby providing a clinically significant measure of the presence of heart failure from the R\ensuremath{-}R intervals alone. Expand
Stochastic feedback and the regulation of biological rhythms.
TLDR
A general approach to the question of how biological rhythms spontaneously self-regulate is proposed, based on the concept of "stochastic feedback", by considering at a coarse-grained level the neuroautonomic regulation of the heart rate. Expand
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. Expand
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. Expand
...
1
2
3
4
...