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      Fractal dynamics in physiology: alterations with disease and aging.

      Proceedings of the National Academy of Sciences of the United States of America
      Aging, Animals, Disease, Fractals, Gait, Health, Heart Rate, Humans

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          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.

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          Most cited references33

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          Simple multifractal cascade model for fully developed turbulence.

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            Long-range anticorrelations and non-Gaussian behavior of the heartbeat.

            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(4) heart beats). Furthermore, we find that the histogram for the heartbeat intervals increments is well described by a Lévy 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.
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              ESTIMATORS FOR LONG-RANGE DEPENDENCE: AN EMPIRICAL STUDY

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                Author and article information

                Journal
                11875196
                128562
                10.1073/pnas.012579499

                Chemistry
                Aging,Animals,Disease,Fractals,Gait,Health,Heart Rate,Humans
                Chemistry
                Aging, Animals, Disease, Fractals, Gait, Health, Heart Rate, Humans

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