Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series
TL;DR: 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.
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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.
Abstract: According to classical concepts of physiologic control, healthy systems are self-regulated to reduce variability and maintain physiologic constancy. Contrary to the predictions of homeostasis, however, the output of a wide variety of systems, such as the normal human heartbeat, fluctuates in a complex manner, even under resting conditions. Scaling techniques adapted from statistical physics reveal the presence of long-range, power-law correlations, as part of multifractal cascades operating over a wide range of time scales. These scaling properties suggest that the nonlinear regulatory systems are operating far from equilibrium, and that maintaining constancy is not the goal of physiologic control. In contrast, for subjects at high risk of sudden death (including those with heart failure), fractal organization, along with certain nonlinear interactions, breaks down. 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. Similar approaches show promise in assessing other regulatory systems, such as human gait control in health and disease. Elucidating the fractal and nonlinear mechanisms involved in physiologic control and complex signaling networks is emerging as a major challenge in the postgenomic era.
1,905 citations
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.
1,841 citations
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.
Abstract: Recognition of facial expressions is critical to our appreciation of the social and physical environment, with separate emotions having distinct facial expressions. Perception of fearful facial expressions has been extensively studied, appearing to depend upon the amygdala. Disgust-literally 'bad taste'-is another important emotion, with a distinct evolutionary history, and is conveyed by a characteristic facial expression. We have used functional magnetic resonance imaging (fMRI) to examine the neural substrate for perceiving disgust expressions. Normal volunteers were presented with faces showing mild or strong disgust or fear. Cerebral activation in response to these stimuli was contrasted with that for neutral faces. Results for fear generally confirmed previous positron emission tomography findings of amygdala involvement. Both strong and mild expressions of disgust activated anterior insular cortex but not the amygdala; strong disgust also activated structures linked to a limbic cortico-striatal-thalamic circuit. The anterior insula is known to be involved in responses to offensive tastes. The neural response to facial expressions of disgust in others is thus closely related to appraisal of distasteful stimuli.
1,548 citations
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.
Abstract: 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 on evidence for multifractality in a biological dynamical system, the healthy human heartbeat, and show that the multifractal character and nonlinear properties of the healthy heart rate are encoded in the Fourier phases. We uncover a loss of multifractality for a life-threatening condition, congestive heart failure.
1,448 citations
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.
Abstract: We examine the detrended fluctuation analysis (DFA), which is a well-established method for the detection of long-range correlations in time series. We show that deviations from scaling which appear at small time scales become stronger in higher orders of DFA, and suggest a modified DFA method to remove them. The improvement is necessary especially for short records that are affected by non-stationarities. Furthermore, we describe how crossovers in the correlation behavior can be detected reliably and determined quantitatively and show how several types of trends in the data affect the different orders of DFA.
1,269 citations
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TL;DR: It is shown that dynamical systems with spatial degrees of freedom naturally evolve into a self-organized critical point, and flicker noise, or 1/f noise, can be identified with the dynamics of the critical state.
Abstract: We show that dynamical systems with spatial degrees of freedom naturally evolve into a self-organized critical point. Flicker noise, or 1/f noise, can be identified with the dynamics of the critical state. This picture also yields insight into the origin of fractal objects.
6,486 citations
Book•
01 Jan 1971
TL;DR: In this article, the authors present a paperback edition of a distinguished book, originally published by Clarendon Press in 1971, which is at the level at which a graduate student who has studied condensed matter physics can begin to comprehend the nature of phase transitions, which involve the transformation of one state of matter into another.
Abstract: This is a paperback edition of a distinguished book, originally published by Clarendon Press in 1971. It was then the first text on critical phenomena, a field that has enjoyed great activity for the past twenty years and that still continues to attract much attention. The book is at the level at which a graduate student who has studied condensed matter physics can begin to comprehend the nature of phase transitions, which involve the transformation of one state of matter into another. (A simple example is the melting of a solid to become a liquid.) Such a transformation is termed 'critical' when, after a certain amount of the substance changes phase, the entire bulk virtually instantaneously also makes the transition. A second, updated edition is planned for future publication, but in the mean time this paperback reissue will be useful in teaching the fundamental principles of this extremely interesting subject.
4,770 citations
1,497 citations
TL;DR: This work proposes a method for studying the stochastic properties of nucleotide sequences by constructing a 1:1 map of the nucleotide sequence onto a walk, which it refers to as a 'DNA walk', and uncovers a remarkably long-range power law correlation.
Abstract: DNA sequences have been analysed using models, such as an n-step Markov chain, that incorporate the possibility of short-range nucleotide correlations. We propose here a method for studying the stochastic properties of nucleotide sequences by constructing a 1:1 map of the nucleotide sequence onto a walk, which we term a 'DNA walk'. We then use the mapping to provide a quantitative measure of the correlation between nucleotides over long distances along the DNA chain. Thus we uncover in the nucleotide sequence a remarkably long-range power law correlation that implies a new scale-invariant property of DNA. We find such long-range correlations in intron-containing genes and in nontranscribed regulatory DNA sequences, but not in complementary DNA sequences or intron-less genes.
1,314 citations
TL;DR: It is found that the successive increments in the cardiac beat-to-beat intervals of healthy subjects display scale-invariant, long-range anticorrelations (up to 10(4) heart beats), and the different scaling behavior in health and disease must relate to the underlying dynamics of the heartbeat.
Abstract: We find that the successive increments in the cardiac beat-to-beat intervals of healthy subjects display scale-invariant, long-range anticorrelations (up to 10 exp 4 heart beats). Furthermore, we find that the histogram for the heartbeat intervals increments is well described by a Levy (1991) stable distribution. For a group of subjects with severe heart disease, we find that the distribution is unchanged, but the long-range correlations vanish. Therefore, the different scaling behavior in health and disease must relate to the underlying dynamics of the heartbeat.
948 citations