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
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TLDR
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.read more
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References
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Book
The Fractal Geometry of Nature
TL;DR: This book is a blend of erudition, popularization, and exposition, and the illustrations include many superb examples of computer graphics that are works of art in their own right.
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PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.
Ary L. Goldberger,Luís A. Nunes Amaral,Leon Glass,Jeffrey M. Hausdorff,Plamen Ch. Ivanov,Roger G. Mark,Joseph E. Mietus,George B. Moody,Chung-Kang Peng,H. Eugene Stanley +9 more
TL;DR: The newly inaugurated Research Resource for Complex Physiologic Signals (RRSPS) as mentioned in this paper was created under the auspices of the National Center for Research Resources (NCR Resources).
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Exploring complex networks
TL;DR: This work aims to understand how an enormous network of interacting dynamical systems — be they neurons, power stations or lasers — will behave collectively, given their individual dynamics and coupling architecture.
Journal ArticleDOI
Mosaic organization of DNA nucleotides
Chung-Kang Peng,Chung-Kang Peng,Chung-Kang Peng,Sergey V. Buldyrev,Sergey V. Buldyrev,Sergey V. Buldyrev,Shlomo Havlin,Shlomo Havlin,Shlomo Havlin,Michael Simons,Michael Simons,Michael Simons,H. E. Stanley,H. E. Stanley,H. E. Stanley,Ary L. Goldberger,Ary L. Goldberger,Ary L. Goldberger +17 more
TL;DR: This work analyzes two classes of controls consisting of patchy nucleotide sequences generated by different algorithms--one without and one with long-range power-law correlations, finding that both types of sequences are quantitatively distinguishable by an alternative fluctuation analysis method.
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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.