Cardiovascular regulation during sleep quantified by symbolic coupling traces

The different sleep stages modulate the autonomous functions blood pressure and heart rate as well as their complex interactions. The method of symbolic coupling traces (SCT) is used to analyse and quantify time-delayed couplings of these measurements. The SCT is defined by the difference of the symmetric and diametric traces of a bivariate word distribution matrix. It is applied to the signals of healthy controls as well as normo- and hypertensive patients with sleep apneas over night. We found significant different couplings not only between the deep sleep and the other sleep stages (p<0.05, Kruskal-Wallis test) but also between healthy subjects and patients. Thereby, SCT yields additional information which can not be measured by standard parameters of heart rate- and blood pressure variability. The proposed method may help to indicate pathological changes in cardiovascular regulation and also effects of continuous positive airway pressure therapy on the cardiovascular system.

[1]  J. Kurths,et al.  Influence of paced maternal breathing on fetal–maternal heart rate coordination , 2009, Proceedings of the National Academy of Sciences.

[2]  Niels Wessel,et al.  Detection of time-delayed interactions in biosignals using symbolic coupling traces , 2009 .

[3]  Luca Faes,et al.  Mutual nonlinear prediction as a tool to evaluate coupling strength and directionality in bivariate time series: comparison among different strategies based on k nearest neighbors. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Matthäus Staniek,et al.  Symbolic transfer entropy. , 2008, Physical review letters.

[5]  Jürgen Kurths,et al.  Recurrence plots for the analysis of complex systems , 2009 .

[6]  Hagen Malberg,et al.  Nonlinear Methods of Cardiovascular Physics and their Clinical Applicability , 2007, Int. J. Bifurc. Chaos.

[7]  H. Malberg,et al.  Comparison of three methods for beat-to-beat-interval extraction from continuous blood pressure and electrocardiogram with respect to heart rate variability analysis / Vergleich von drei Methoden der Schlag-zu-Schlag-Intervall-Extraktion aus kontinuierlichen Blutdruckverläufen und Elektrokardiogramm , 2006 .

[8]  Rainer Dahlhaus,et al.  Partial phase synchronization for multivariate synchronizing systems. , 2006, Physical review letters.

[9]  P. Castiglioni,et al.  Baroreflex control of heart rate during sleep in severe obstructive sleep apnoea: effects of acute CPAP , 2006, European Respiratory Journal.

[10]  刘金明,et al.  IL-13受体α2降低血吸虫病肉芽肿的炎症反应并延长宿主存活时间[英]/Mentink-Kane MM,Cheever AW，Thompson RW，et al//Proc Natl Acad Sci U S A , 2005 .

[11]  Ioannis G. Kevrekidis,et al.  International Journal of Bifurcation and Chaos in Applied Sciences and Engineering: Editorial , 2005 .

[12]  Ute Feldmann,et al.  Predictability Improvement as an Asymmetrical Measure of Interdependence in bivariate Time Series , 2004, Int. J. Bifurc. Chaos.

[13]  Milan Palus,et al.  Direction of coupling from phases of interacting oscillators: an information-theoretic approach. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  L. Glass.  Synchronization and rhythmic processes in physiology , 2001, Nature.

[15]  J. Kurths,et al.  Nonlinear analysis of complex phenomena in cardiological data , 2000, Herzschrittmachertherapie und Elektrophysiologie.

[16]  Schreiber,et al.  Measuring information transfer , 2000, Physical review letters.

[17]  Bernd Blasius,et al.  Complex dynamics and phase synchronization in spatially extended ecological systems , 1999, Nature.

[18]  G. Breithardt,et al.  Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. , 1996 .

[19]  G. Parati,et al.  Spectral analysis of blood pressure and heart rate variability in evaluating cardiovascular regulation. A critical appraisal. , 1995, Hypertension.

[20]  A Voss,et al.  Improved analysis of heart rate variability by methods of nonlinear dynamics. , 1995, Journal of electrocardiology.

[21]  V. Hombach,et al.  THE NORTH AMERICAN SOCIETY OF PACING AND ELECTROPHYSIOLOGY , 1985, Pacing and clinical electrophysiology : PACE.

[22]  H. Tong.  Non-linear time series. A dynamical system approach , 1990 .

[23]  R. Cohen,et al.  Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. , 1981, Science.

[24]  J. L. Harrison,et al.  The Government Printing Office , 1968, American Journal of Pharmaceutical Education.

[25]  A. Rechtschaffen,et al.  A manual of standardized terminology, technique and scoring system for sleep stages of human subjects , 1968 .

[26]  A. Rechtschaffen.  Techniques and Scoring System for Sleep Stages of Human Subjects , 1968 .