The dimension of chaos in the fetal heart rate

Chaffin, David G.; Goldberg, Cynthia C.; Reed, Kathryn L.

doi:10.1016/0002-9378(91)90384-4

Cited by 35 publications

(26 citation statements)

References 3 publications

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“…rhythms has been based largely on observations of the 1/f or fractal characteristics in the power spectrum and on measurements of the correlation dimension of reconstructed attractors (2,3,6,8,(30)(31)(32). Such evidence is consistent with the hypothesis that human heart rhythms are driven by nonlinear and possibly chaotic processes.…”

Section: Analytical Methods Empirical Evidence For Nonlinear Behaviormentioning

confidence: 54%

Nonlinear control of heart rate variability in human infants.

Sugihara

Allan

Sobel

et al. 1996

Proc. Natl. Acad. Sci. U.S.A.

144

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Nonlinear analyses of infant heart rhythms reveal a marked rise in the complexity of the electrocardiogram with maturation. We find that normal mature infants (gestation 2 35 weeks) have complex and distinctly nonlinear heart rhythms (consistent with recent reports for healthy adults) but that such nonlinearity is lacking in preterm infants (gestation ' 27 weeks) where parasympatheticsympathetic interaction and function are presumed to be less well developed. Our study further shows that infants with clinical brain death and those treated with atropine exhibit a similar lack of nonlinear feedback control. These three lines of evidence support the hypothesis championed by Goldberger et al. [Goldberger, A. L., Rigney, D. R. & West, B. J. (1990) Sci. Am. 262,[43][44][45][46][47][48][49] that autonomic nervous system control underlies the nonlinearity and possible chaos of normal heart rhythms. This report demonstrates 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. It parallels earlier work documenting changes in the variability of heart rhythms in each of these cases and suggests that nonlinearity may provide additional power in characterizing physiological states.Contrary to conventional wisdom, recent evidence suggests that sinus heart rhythms in normal human adults are not strictly regular but have a complex variability that is consistent with nonlinear feedback and possible chaost (1-10). Moreover, such variability appears to be greatly reduced or virtually absent in adults with heart disease and in older adults (>70 yr), where simpler and sometimes cyclic rhythms tend to predominate (7)(8)(9)(10)(13)(14)(15). It is hypothesized that in the healthy adult, chaotic-like dynamics arise from nonlinear feedback created by the interaction of sympathetic and parasympathetic inputs to the sinoatrial node (2-4, 7, 8). According to this hypothesis, heart disease and aging may be associated with a loss of such adaptability and feedback control (8-10). Recent studies of the power spectrum of sinus rhythm heart rate variability by Akselrod and others (16-18) have suggested that this feedback control is not fully developed in infants due to a relative lag in maturation of the parasympathetic influence (19,20). In a similar vein, have shown that heart-rate variability increases in the first three days of life in free-breathing premature infants (27-32 weeks gestation), and Szeto et al. (21) have shown an increase in 1/f complexity of intrauterine "breathing" (diaphragm movements) during maturation of the lamb fetus. Because feedback control should not be present in early gestational infants (22), we reasoned that sequential studies of heart rate variability in the neonatal period might reveal the development of nonlinear feedback and chaotic-like dynamics. Similarly, insofar as balanced autonomic control is needed to produce normal heart-rate variability, we would expect that nonlinearity would be a...

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Section: Analytical Methods Empirical Evidence For Nonlinear Behaviormentioning

confidence: 54%

Nonlinear control of heart rate variability in human infants.

Sugihara

Allan

Sobel

et al. 1996

Proc. Natl. Acad. Sci. U.S.A.

144

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“…Techniques of phase-space reconstruction and dimensional analysis were applied to HR traces obtained from scalp electrodes in 12 normal foetuses by Chaffin et al (1991).…”

Section: Introductionmentioning

confidence: 99%

Methods derived from nonlinear dynamics for analysing heart rate variability

Voss

Schulz

Schroeder

et al. 2008

Phil. Trans. R. Soc. A.

519

417

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Methods from nonlinear dynamics (NLD) have shown new insights into heart rate (HR) variability changes under various physiological and pathological conditions, providing additional prognostic information and complementing traditional time-and frequencydomain analyses. In this review, some of the most prominent indices of nonlinear and fractal dynamics are summarized and their algorithmic implementations and applications in clinical trials are discussed. Several of those indices have been proven to be of diagnostic relevance or have contributed to risk stratification. In particular, techniques based on mono-and multifractal analyses and symbolic dynamics have been successfully applied to clinical studies. Further advances in HR variability analysis are expected through multidimensional and multivariate assessments. Today, the question is no longer about whether or not methods from NLD should be applied; however, it is relevant to ask which of the methods should be selected and under which basic and standardized conditions should they be applied.

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“…The feasibility of dimensional analysis was thus demonstrated by Chaffin et al [8]. Also, on the basis of ApEn, a reduction in heart rate complexity could be shown in fetuses with acidosis and distress [3].…”

Section: Discussionmentioning

confidence: 99%

“…The complexity measures ApD1 and ApEn characterize the scaling (static) properties of the distribution as well as the expansion behavior (dynamical properties) of the generating dynamics. Methods used in the determination of the approximate dimension and approximate entropy have been described elsewhere [2,[6][7][8]. Apart from the original definitions, we used a strictly local approach for the approximation of the information dimension and the Kolmogorov entropy.…”

Section: Methodsmentioning

confidence: 99%