TY  - JOUR
A1  - Wessel, Niels
A1  - Voss, Andreas
A1  - Malberg, Hagen
A1  - Ziehmann, Christine
A1  - Voss, Henning U.
A1  - Schirdewan, Alexander
A1  - Meyerfeldt, Udo
A1  - Kurths, Jürgen
T1  - Nonlinear analysis of complex phenomena in cardiological data
N2  - The main intention of this contribution is to discuss different nonlinear approaches to heart rate and blood pressure variability analysis for a better understanding of the cardiovascular regulation. We investigate measures of complexity which are based on symbolic dynamics, renormalised entropy and the finite time growth rates. The dual sequence method to estimate the baroreflex sensitivity and the maximal correlation method to estimate the nonlinear coupling between time series are employed for analysing bivariate data. The latter appears to be a suitable method to estimate the strength of the nonlinear coupling and the coupling direction. Heart rate and blood pressure data from clinical pilot studies and from very large clinical studies are analysed. We demonstrate that parameters from nonlinear dynamics are useful for risk stratification after myocardial infarction, for the prediction of life-threatening cardiac events even in short time series, and for modelling the relationship between heart rate and blood pressure regulation. These findings could be of importance for clinical diagnostics, in algorithms for risk stratification, and for therapeutic and preventive tools of next generation implantable cardioverter defibrillators.
Y1  - 2000
ER  - 
TY  - JOUR
A1  - Timmer, Jens
A1  - Schwarz, Udo
A1  - Voss, Henning U.
A1  - Wardinski, Ingo
A1  - Belloni, Tomaso
A1  - Hasinger, Günther
A1  - VanDerKlis, Michael
A1  - Kurths, Jürgen
T1  - Linear and Nonlinear Time Series Analysis of the Black Hole Candidate Cygnus X-1
N2  - We analyze the variability in the x-ray lightcurves of the black hole candidate Cygnus X-1 by linear and nonlinear time series analysis methods. While a linear model describes the overall second order properties of the observed data well, surrogate data analysis reveals a significant deviation from linearity. We discuss the relation between shot noise models usually applied to analyze these data and linear stochastic autoregressive models. We debate statistical and interpretational issues of surrogate data testing for the present context. Finally, we suggest a combination of tools from linear and nonlinear time series analysis methods as a procedure to test the predictions of astrophysical models on observed data.
Y1  - 2000
UR  - http://pre.aps.org/
ER  -