Nonlinear dynamics in sudden cardiac death syndrome: Heartrate oscillations and bifurcations

Goldberger, Ary L.; Rigney, David R.; Mietus, Joseph E.; Antman, Elliott M.; Greenwald, Scott

doi:10.1007/bf01939894

Cited by 201 publications

(83 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Assessing correlations under pathologic conditions is likely to be particularly informative for patients with congestive heart failure since these individuals have abnormalities in both the sympathetic and parasympathetic control mechanisms [21] that regulate beat-to-beat variability. Previous studies have demonstrated marked changes in short-range heart rate dynamics in heart failure compared to healthy function, including the emergence of intermittent relatively low frequency (~ 1 cycle/minute) heart rate oscillations associated with the well-recognized syndrome of periodic (Cheyne-Stokes) respiration, an abnormal breathing pattern often associated with low cardiac output [21].…”

Section: Alteration Of Correlation Properties In Pathologic Statesmentioning

confidence: 99%

“…Previous studies have demonstrated marked changes in short-range heart rate dynamics in heart failure compared to healthy function, including the emergence of intermittent relatively low frequency (~ 1 cycle/minute) heart rate oscillations associated with the well-recognized syndrome of periodic (Cheyne-Stokes) respiration, an abnormal breathing pattern often associated with low cardiac output [21]. Of note is the fact that patients with congestive heart failure are at very high risk for sudden cardiac death.…”

Section: Alteration Of Correlation Properties In Pathologic Statesmentioning

confidence: 99%

“…Time series of beat-to-beat heart rate intervals obtained from digitized electrocardiograms are known to be nonstationary and exhibit extremely complex behavior [33][34][35]. A typical feature of these signals is the presence of "patchy" patterns which change over time.…”

Section: Wavelet Analysis Of Heartbeat Intervalsmentioning

confidence: 99%

See 2 more Smart Citations

Monofractal and multifractal approaches to complex biomedical signals

Stanley

2000

AIP Conference Proceedings

View full text Add to dashboard Cite

Abstract. Even under healthy, basal conditions, physiologic systems show erratic fluctuations resembling those found in dynamical systems driven away from an equilibrium state. Do such "nonequilibrium" fluctuations simply reflect the fact that physiologic systems are being constantly perturbed by external and intrinsic uncorrelated noise? Or, do these fluctuations actually contain "hidden" information about the underlying nonequilibrium control mechanisms? We report some recent attempts to understand the dynamics of complex physiologic fluctuations by adapting and extending concepts and methods developed very recently in statistical physics. Specifically, we focus on interbeat interval variability as an important quantity to help elucidate possibly nonhomeostatic physiologic variability because (i) the heart rate is under direct neuroautonomic control, (ii) interbeat interval variability is readily measured by noninvasive means, and (iii) analysis of these heart rate dynamics may provide important practical diagnostic and prognostic information not obtainable with current approaches. The analytic tools we discuss may be used on a wider range of physiologic signals. We first review recent progress using two analysis methods-detrended fluctuation analysis and wavelets-appropriate for quantifying monofractal structures. We then describe very recent work that quantifies multifractal features of interbeat interval series, and the discovery that the multifractal structure of healthy subjects is different from that of diseased subjects. We also discuss the application of fractal scaling analysis to the dynamics of heartbeat regulation, and report the recent finding that the scaling exponent a is smaller during sleep periods compared to wake periods.

show abstract

Section: Alteration Of Correlation Properties In Pathologic Statesmentioning

confidence: 99%

Section: Alteration Of Correlation Properties In Pathologic Statesmentioning

confidence: 99%

See 1 more Smart Citation

Monofractal and multifractal approaches to complex biomedical signals

Stanley

2000

AIP Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…Accordingly, first applications of nonlinear dynamics tools in medical diagnostics have been met with success over the last decade [Focus Issue: Dynamical Disease: Mathematical Analysis of Human Illness, 1995; Kantz et al, 1998]. So far, however, research was limited either to only analyze data [Goldberger et al, 1988;Yamamoto & Hughson, 1994a;Cerutti et al, 1996;Poon & Merrill, 1997;Ivanov et al, 1999;Schmidt et al, 1999a;Yang et al, 2003;Wessel et al, 2004c], or develop models [Garfinkel et al, 1992;Wikswo et al, 1995;Gray et al, 1998;Witkowski et al, 1998;Ditto & Showalter, 1998 Heart, 2003]. A further aim of this tutorial, therefore, is, to go a qualitatively new step: the combination of data analysis and modeling.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Methods of Cardiovascular Physics and Their Clinical Applicability

Wessel

Malberg²,

Bauernschmitt

et al. 2007

Int. J. Bifurcation Chaos

102

107

View full text Add to dashboard Cite

In this tutorial we present recently developed nonlinear methods of cardiovascular physics and show their potentials to clinically relevant problems in cardiology. The first part describes methods of cardiovascular physics, especially data analysis and modeling of noninvasively measured biosignals, with the aim to improve clinical diagnostics and to improve the understanding of cardiovascular regulation. Applications of nonlinear data analysis and modeling tools are various and outlined in the second part of this tutorial: monitoring-, diagnosis-, course and mortality prognoses as well as early detection of heart diseases. We show, that these data analyses and modeling methods lead to significant improvements in different medical fields.Keywords: Cardiovascular physics; nonlinear data analysis and modeling; heart rate and blood pressure variability; baroreflex sensitivity. List of Abbreviations

show abstract

“…ANOVAs may not capture priming effects in children because their reaction times are more variable than those of adults. Younger people's high variability has also been found in the heart and in other physiological systems (Goldberger, Rigney, Mietus, Antman, & Greenwald, 1988;Goldberger, Rigney, & West, 1990;.…”

mentioning

confidence: 98%

Development of Memory Structures for Homographs Using Pathfinder Network Representations

Nievas

Justicia

2003

Span. J. Psychol.

View full text Add to dashboard Cite

Some studies with children have shown that there is no semantic priming at short stimulus onset asynchrony (SOA) in lexical decision and naming tasks for homographs. The predictions of spreading activation theories might explain this missing effect. There may be differences in children's and adults' memory structures. We have explored this hypothesis. The development of memory structure representations for homographs was measured by a Pathfinder algorithm. In Experiment 1, the three dependent variables were: the number of links in the network, closeness measures (C), and distances between nodes. Results revealed developmental differences in network structure representations in adults and children. In Experiment 2, results revealed that these differences were not due to the cohort effect. In Experiment 3, the relationship between associative strength, as measured by associative norms, and distances, as measured by Pathfinder algorithm, was explored. The results of these three experiments and empirical research from semantic priming experiments show that these differences in memory structure representations could be one of the sources of the missing semantic priming effect in children. Keywords: Pathfinder, memory structure representations, semantic priming, cohort effect Algunos estudios con niños han mostrado que no existe facilitación semántica, con intervalos de tiempo cortos, en tareas de decisión léxica y en nombrar en homógrafos. Las predicciones de las teorías de difusión de la activación podrían explicar la ausencia de este efecto. Podría haber diferencias en las estructuras de memoria entre niños y adultos. Nosotros hemos explorado esta hipótesis. El desarrollo de las representaciones de estructuras de memoria para homógrafos se midió por el algoritmo Pathfinder. En el primer experimento, las tres variables dependientes fueron: el número de conexiones en la estructura, las medidas C y las distancias entre nodos. Los resultados revelaron diferencias evolutivas en las representaciones de las estructuras de red entre niños y adultos. En el experimento 2, los resultados mostraron que estas diferencias no eran debidas al efecto de cohorte. En el experimento 3, se exploró la relación entre la fuerza asociativa, medida por las normas de asociación, y las distancias, como medida del algoritmo Pathfinder. Los resultados de estos tres experimentos y la investigación empírica de los experimentos de facilitación semántica muestran que estas diferencias en las representaciones de estructuras de memoria podrían ser una de las fuentes para explicar la ausencia de facilitación semántica en niños. Palabras clave: Pathfinder, representaciones de estructuras de memoria, facilitación semántica, efecto cohorte

show abstract

Nonlinear dynamics in sudden cardiac death syndrome: Heartrate oscillations and bifurcations

Abstract: Patients at high risk of sudden cardiac death show evidence of nonlinear heartrate dynamics, including abrupt spectral changes (bifurcations) and sustained low frequency (.01-.04 Hz) oscillations in heartrate.

Cited by 201 publications

References 16 publications

Monofractal and multifractal approaches to complex biomedical signals

Monofractal and multifractal approaches to complex biomedical signals

Nonlinear Methods of Cardiovascular Physics and Their Clinical Applicability

Development of Memory Structures for Homographs Using Pathfinder Network Representations

Contact Info

Product

Resources

About