Journal ArticleDOI
Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series
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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.Abstract:
The healthy heartbeat is traditionally thought to be regulated according to the classical principle of homeostasis whereby physiologic systems operate to reduce variability and achieve an equilibrium-like state [Physiol. Rev. 9, 399-431 (1929)]. However, recent studies [Phys. Rev. Lett. 70, 1343-1346 (1993); Fractals in Biology and Medicine (Birkhauser-Verlag, Basel, 1994), pp. 55-65] reveal that under normal conditions, beat-to-beat fluctuations in heart rate display the kind of long-range correlations typically exhibited by dynamical systems far from equilibrium [Phys. Rev. Lett. 59, 381-384 (1987)]. In contrast, heart rate time series from patients with severe congestive heart failure show a breakdown of this long-range correlation behavior. We describe a new method--detrended fluctuation analysis (DFA)--for quantifying this correlation property in non-stationary physiological time series. Application of this technique shows evidence for a crossover phenomenon associated with a change in short and long-range scaling exponents. This method may be of use in distinguishing healthy from pathologic data sets based on differences in these scaling properties.read more
Citations
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Fractal dynamics in physiology: Alterations with disease and aging
Ary L. Goldberger,Luís A. Nunes Amaral,Jeffrey M. Hausdorff,Plamen Ch. Ivanov,C.-K. Peng,H. Eugene Stanley +5 more
TL;DR: Application of fractal analysis may provide new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as to monitoring the aging process, and similar approaches show promise in assessing other regulatory systems, such as human gait control in health and disease.
Journal ArticleDOI
Kubios HRV - Heart rate variability analysis software
Mika P. Tarvainen,Juha-Pekka Niskanen,Jukka A. Lipponen,Perttu O. Ranta-aho,Pasi A. Karjalainen +4 more
TL;DR: Kubios HRV is an advanced and easy to use software for heart rate variability (HRV) analysis that includes an adaptive QRS detection algorithm and tools for artifact correction, trend removal and analysis sample selection.
Journal ArticleDOI
A specific neural substrate for perceiving facial expressions of disgust
Mary L. Phillips,Andrew W. Young,Carl Senior,Michael Brammer,Christopher Andrew,Andrew J. Calder,Edward T. Bullmore,David I. Perrett,Duncan Rowland,Steven Williams,Jeffrey A. Gray,Anthony S. David +11 more
TL;DR: Functional magnetic resonance imaging was used to examine the neural substrate for perceiving disgust expressions and found the neural response to facial expressions of disgust in others is thus closely related to appraisal of distasteful stimuli.
Journal ArticleDOI
Multifractality in human heartbeat dynamics
Plamen Ch. Ivanov,Plamen Ch. Ivanov,Luís A. Nunes Amaral,Luís A. Nunes Amaral,Ary L. Goldberger,Shlomo Havlin,Michael Rosenblum,Zbigniew R. Struzik,H. Eugene Stanley +8 more
TL;DR: In this paper, the authors 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.
Journal ArticleDOI
Detecting long-range correlations with detrended fluctuation analysis
TL;DR: It is shown that deviations from scaling which appear at small time scales become stronger in higher orders of detrended fluctuation analysis, and a modified DFA method is suggested to remove them.
References
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Finite-size effects on long-range correlations: Implications for analyzing DNA sequences
Chung-Kang Peng,Sergey V. Buldyrev,Ary L. Goldberger,Shlomo Havlin,Michael Simons,Michael Simons,H. E. Stanley +6 more
TL;DR: It is found that the DNA exponent fluctuations are consistent with those obtained from the control sequences having long-range power-law correlations, and the original "DNA-walk" method is intrinsically more accurate due to reduced noise.