The application of methods of non-linear dynamics for the improved and predictive recognition of patients threatened by sudden cardiac death

Voss, Andreas; Kurths, Jüergen; Kleiner, H.J.; Witt, Annette; Wessel, Niels; Saparin, Peter; Osterziel, Karl‐Josef; Schurath, Ronald; Dietz, Rainer

doi:10.1016/s0008-6363(96)00008-9

Cited by 323 publications

(267 citation statements)

References 29 publications

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“…However, as stated in the introduction, a decreased LLE is associated with different CNS disorders and appears to indicate a decrease in flexibility in cardiovascular control. This may be related to some aspect of vagal function and may further explain the higher incidence of significant cardiovascular events and sudden cardiac death (Voss et al, 1996;Ho et al, 1997). In this context, our previous findings of decreased LLE in patients compared to control subjects in supine as well as standing postures (P-0.00001) is of special interest.…”

Section: Discussionmentioning

confidence: 80%

“…Recent literature has shown the utility of nonlinear measures of heart rate (HR) variability to study cardiac autonomic function in health and disease (Goldberger and West, 1987;Katz, 1988;Glenny et al, 1991;Pincus et al, 1991;Yeragani et al, 1993bYeragani et al, , 1997Guzzetti et al, 1996;Lombardi et al, 1996;Voss et al, 1996;Ho et al, 1997;Braun et al, 1998;Storella et al, 1998;Kagiyama et al, 1999;Silipo et al, 1999;Yeragani et al, 2000). Analysis of time series using methods of non-linear dynamics can be performed by the estimation of Lyapunov exponents (LE) and degree of non-linearity (NL).…”

Section: Introductionmentioning

confidence: 99%

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Heart rate time series: decreased chaos after intravenous lactate and increased non-linearity after isoproterenol in normal subjects

Yeragani

Rao

Jayaraman

et al. 2002

Psychiatry Research

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In this study, we reanalyzed our previous heart rate time series data on the effects of intravenous sodium lactate (ns9) and intravenous isoproterenol (ns11) using non-linear techniques. Our prior findings of significantly higher baseline non-linear scores (NL: S ) and significantly lower largest Lyapunov exponents in supine posture in netGS patients with panic disorder compared to control subjects prompted this study. We obtained the largest Lyapunov exponent (LLE), and a measure of non-linearity (NL: S ) of heart rate time series. LLE quantifies predictability netGS and NL quantifies the deviation from linear processes. There was a significant increase in NL score, (S ) after netGS isoproterenol infusions and a significant decrease in LLE (an increase in predictability indicating decreased chaos), after intravenous lactate in supine posture in normal control subjects. Increased NL scores in supine posture after intravenous isoproterenol may be due to a relative increase in cardiac sympathetic activity or a decrease in vagal activity at least in certain circumstances, and an overall decrease in LLE may indicate an impaired cardiac autonomic flexibility after intravenous sodium lactate, as LLE is diminished by autonomic blockade by atropine. Band analysis of LLE (LFyHF) (LF: 0.04 -0.15 Hz and HF: 0.15 -0.5 Hz) showed an increase of these ratios during either condition with a higher sympathovagal interaction after the drug administration. These findings may throw new light on the association of anxiety and significant cardiovascular events. ᮊ

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Section: Discussionmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Heart rate time series: decreased chaos after intravenous lactate and increased non-linearity after isoproterenol in normal subjects

Yeragani

Rao

Jayaraman

et al. 2002

Psychiatry Research

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“…A triangular index HRVi showing reduced HRV has been associated with both arrhythmic and nonarrhythmic death [Task Force Heart Rate Variability, 1996;Hartikainen et al, 1996]. We introduced a more robust method to quantify the distribution [Voss et al, 1996b] based on information theory, in particular the method uses the Shannon-and the Renyi-entropy of the histogram. We demonstrated the usefulness for risk stratification two years later in a blinded study ].…”

Section: Time and Frequency Domain Parametermentioning

confidence: 99%

“…Therefore, we favor measures of complexityanother approach within nonlinear dynamicswhich are able to quantitatively characterize the dynamics even for rather short time series [Schwarz et al, 1993;Kurths et al, 1995;Voss et al, 1996b;Voss et al, 1998;Wessel et al, 2000c].…”

Section: Introductionmentioning

confidence: 99%

“…We have recently demonstrated that a multivariate approach with HRV parameters including nonlinear methods as well as the combination of HRV measures with clinical parameters like the ejection fraction, the complexity of ventricular arrhythmias or the signal-averaged electrocardiogram, significantly improves the results of risk stratification ]. Moreover, in numerous clinical studies [Barron & Lesh, 1996;Lombardi et al, 1996b;Lombardi et al, 1996a;Voss et al, 1996b;La Rovere & Schwartz, 1997;La Rovere et al, 2001] it was demonstrated, that a multiparametric analysis of the cardiovascular regulation increases the diagnostic information. However, one has to consider some characteristics when using mathematical approaches for the analysis for physiological systems (MILHORN [Milhorn, 1966]).…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear Methods of Cardiovascular Physics and Their Clinical Applicability

Wessel

Malberg²,

Bauernschmitt

et al. 2007

Int. J. Bifurcation Chaos

100

107

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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

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Nonlinear measures of heart period variability: Decreased measures of symbolic dynamics in patients with panic disorder

et al. 2000

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Time series of heart period are not linear and recent studies illustrated the importance of using nonlinear methods to quantify the complexity of these time series. We compared different techniques to quantify the nonlinear complexity of these time series in patients with panic disorder and normal controls and correlated these measures with spectral powers in different bands of interest. Twenty‐four hour ECG was recorded in 23 normal controls and 29 patients with panic disorder by using Holter records. Time series of heart period were analyzed by using approximate entropies, slopes of 1/f scaling, two algorithms to calculate fractal dimension, and word sequences using symbolic dynamics. Measures using symbolic dynamics, especially word count (WC‐100), showed highly significant differences between the two groups similar to some of the frequency domain (spectral) measures, while the other techniques were relatively ineffective to distinguish between the two groups. Different nonlinear techniques may relate to different aspects of nonlinear complexity of the time series. These nonlinear techniques were also not uniform in showing the differences between awake and sleep periods. Some correlate with the measures of respiratory sinus arrhythmia and some measures obtained from symbolic dynamics may reflect not only the nonlinear complexity of the time series but also the total variability in the 24 hr HP time series, especially power in the ultra‐low frequency band (<0.0033 Hz). However, word count (WC‐100) had only weak correlations with other measures and discriminated best between the two groups and showed that this nonlinear measure was of additional value to the linear measures in classifying the two groups. Depression and Anxiety 12:67–77, 2000. © 2000 Wiley‐Liss, Inc.

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The application of methods of non-linear dynamics for the improved and predictive recognition of patients threatened by sudden cardiac death

Cited by 323 publications

References 29 publications

Heart rate time series: decreased chaos after intravenous lactate and increased non-linearity after isoproterenol in normal subjects

Heart rate time series: decreased chaos after intravenous lactate and increased non-linearity after isoproterenol in normal subjects

Nonlinear Methods of Cardiovascular Physics and Their Clinical Applicability

Nonlinear measures of heart period variability: Decreased measures of symbolic dynamics in patients with panic disorder

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