TY - JOUR A1 - Topçu, Çağdaş A1 - Frühwirth, Matthias A1 - Moser, Maximilian A1 - Rosenblum, Michael A1 - Pikovskij, Arkadij T1 - Disentangling respiratory sinus arrhythmia in heart rate variability records JF - Physiological Measurement N2 - Objective: Several different measures of heart rate variability, and particularly of respiratory sinus arrhythmia, are widely used in research and clinical applications. For many purposes it is important to know which features of heart rate variability are directly related to respiration and which are caused by other aspects of cardiac dynamics. Approach: Inspired by ideas from the theory of coupled oscillators, we use simultaneous measurements of respiratory and cardiac activity to perform a nonlinear disentanglement of the heart rate variability into the respiratory-related component and the rest. Main results: The theoretical consideration is illustrated by the analysis of 25 data sets from healthy subjects. In all cases we show how the disentanglement is manifested in the different measures of heart rate variability. Significance: The suggested technique can be exploited as a universal preprocessing tool, both for the analysis of respiratory influence on the heart rate and in cases when effects of other factors on the heart rate variability are in focus. KW - respiratory sinus arrhythmia KW - heart rate variability KW - coupled oscillators model KW - phase dynamics KW - data analysis Y1 - 2018 U6 - https://doi.org/10.1088/1361-6579/aabea4 SN - 0967-3334 SN - 1361-6579 VL - 39 IS - 5 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Rosenblum, Michael A1 - Frühwirth, Martha A1 - Moser, Maximilian A1 - Pikovskij, Arkadij T1 - Dynamical disentanglement in an analysis of oscillatory systems: an application to respiratory sinus arrhythmia JF - Philosophical Transactions of the Royal Society of London, Series A : Mathematical, Physical and Engineering Sciences N2 - We develop a technique for the multivariate data analysis of perturbed self-sustained oscillators. The approach is based on the reconstruction of the phase dynamics model from observations and on a subsequent exploration of this model. For the system, driven by several inputs, we suggest a dynamical disentanglement procedure, allowing us to reconstruct the variability of the system's output that is due to a particular observed input, or, alternatively, to reconstruct the variability which is caused by all the inputs except for the observed one. We focus on the application of the method to the vagal component of the heart rate variability caused by a respiratory influence. We develop an algorithm that extracts purely respiratory-related variability, using a respiratory trace and times of R-peaks in the electrocardiogram. The algorithm can be applied to other systems where the observed bivariate data can be represented as a point process and a slow continuous signal, e.g. for the analysis of neuronal spiking. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'. KW - phase dynamics KW - point process KW - vagal sympathetic activity KW - autonomic nervous system Y1 - 2019 U6 - https://doi.org/10.1098/rsta.2019.0045 SN - 1364-503X SN - 1471-2962 VL - 377 IS - 2160 PB - Royal Society CY - London ER - TY - GEN A1 - Topçu, Çağdaş A1 - Frühwirth, Matthias A1 - Moser, Maximilian A1 - Rosenblum, Michael A1 - Pikovskij, Arkadij T1 - Disentangling respiratory sinus arrhythmia in heart rate variability records T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Objective: Several different measures of heart rate variability, and particularly of respiratory sinus arrhythmia, are widely used in research and clinical applications. For many purposes it is important to know which features of heart rate variability are directly related to respiration and which are caused by other aspects of cardiac dynamics. Approach: Inspired by ideas from the theory of coupled oscillators, we use simultaneous measurements of respiratory and cardiac activity to perform a nonlinear disentanglement of the heart rate variability into the respiratory-related component and the rest. Main results: The theoretical consideration is illustrated by the analysis of 25 data sets from healthy subjects. In all cases we show how the disentanglement is manifested in the different measures of heart rate variability. Significance: The suggested technique can be exploited as a universal preprocessing tool, both for the analysis of respiratory influence on the heart rate and in cases when effects of other factors on the heart rate variability are in focus. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 913 KW - respiratory sinus arrhythmia KW - heart rate variability KW - coupled oscillators model KW - phase dynamics KW - data analysis Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-436315 SN - 1866-8372 IS - 913 ER - TY - THES A1 - Schwabedal, Justus Tilmann Caspar T1 - Phase dynamics of irregular oscillations N2 - In der vorliegenden Dissertation wird eine Beschreibung der Phasendynamik irregulärer Oszillationen und deren Wechselwirkungen vorgestellt. Hierbei werden chaotische und stochastische Oszillationen autonomer dissipativer Systeme betrachtet. Für eine Phasenbeschreibung stochastischer Oszillationen müssen zum einen unterschiedliche Werte der Phase zueinander in Beziehung gesetzt werden, um ihre Dynamik unabhängig von der gewählten Parametrisierung der Oszillation beschreiben zu können. Zum anderen müssen für stochastische und chaotische Oszillationen diejenigen Systemzustände identifiziert werden, die sich in der gleichen Phase befinden. Im Rahmen dieser Dissertation werden die Werte der Phase über eine gemittelte Phasengeschwindigkeitsfunktion miteinander in Beziehung gesetzt. Für stochastische Oszillationen sind jedoch verschiedene Definitionen der mittleren Geschwindigkeit möglich. Um die Unterschiede der Geschwindigkeitsdefinitionen besser zu verstehen, werden auf ihrer Basis effektive deterministische Modelle der Oszillationen konstruiert. Hierbei zeigt sich, dass die Modelle unterschiedliche Oszillationseigenschaften, wie z. B. die mittlere Frequenz oder die invariante Wahrscheinlichkeitsverteilung, nachahmen. Je nach Anwendung stellt die effektive Phasengeschwindigkeitsfunktion eines speziellen Modells eine zweckmäßige Phasenbeziehung her. Wie anhand einfacher Beispiele erklärt wird, kann so die Theorie der effektiven Phasendynamik auch kontinuierlich und pulsartig wechselwirkende stochastische Oszillationen beschreiben. Weiterhin wird ein Kriterium für die invariante Identifikation von Zuständen gleicher Phase irregulärer Oszillationen zu sogenannten generalisierten Isophasen beschrieben: Die Zustände einer solchen Isophase sollen in ihrer dynamischen Entwicklung ununterscheidbar werden. Für stochastische Oszillationen wird dieses Kriterium in einem mittleren Sinne interpretiert. Wie anhand von Beispielen demonstriert wird, lassen sich so verschiedene Typen stochastischer Oszillationen in einheitlicher Weise auf eine stochastische Phasendynamik reduzieren. Mit Hilfe eines numerischen Algorithmus zur Schätzung der Isophasen aus Daten wird die Anwendbarkeit der Theorie anhand eines Signals regelmäßiger Atmung gezeigt. Weiterhin zeigt sich, dass das Kriterium der Phasenidentifikation für chaotische Oszillationen nur approximativ erfüllt werden kann. Anhand des Rössleroszillators wird der tiefgreifende Zusammenhang zwischen approximativen Isophasen, chaotischer Phasendiffusion und instabilen periodischen Orbits dargelegt. Gemeinsam ermöglichen die Theorien der effektiven Phasendynamik und der generalisierten Isophasen eine umfassende und einheitliche Phasenbeschreibung irregulärer Oszillationen. N2 - Many natural systems embedded in a complex surrounding show irregular oscillatory dynamics. The oscillations can be parameterized by a phase variable in order to obtain a simplified theoretical description of the dynamics. Importantly, a phase description can be easily extended to describe the interactions of the system with its surrounding. It is desirable to define an invariant phase that is independent of the observable or the arbitrary parameterization, in order to make, for example, the phase characteristics obtained from different experiments comparable. In this thesis, we present an invariant phase description of irregular oscillations and their interactions with the surrounding. The description is applicable to stochastic and chaotic irregular oscillations of autonomous dissipative systems. For this it is necessary to interrelate different phase values in order to allow for a parameterization-independent phase definition. On the other hand, a criterion is needed, that invariantly identifies the system states that are in the same phase. To allow for a parameterization-independent definition of phase, we interrelate different phase values by the phase velocity. However, the treatment of stochastic oscillations is complicated by the fact that different definitions of average velocity are possible. For a better understanding of their differences, we analyse effective deterministic phase models of the oscillations based upon the different velocity definitions. Dependent on the application, a certain effective velocity is suitable for a parameterization-independent phase description. In this way, continuous as well pulse-like interactions of stochastic oscillations can be described, as it is demonstrated with simple examples. On the other hand, an invariant criterion of identification is proposed that generalizes the concept of standard (Winfree) isophases. System states of the same phase are identified to belong to the same generalized isophase using the following invariant criterion: All states of an isophase shall become indistinguishable in the course of time. The criterion is interpreted in an average sense for stochastic oscillations. It allows for a unified treatment of different types of stochastic oscillations. Using a numerical estimation algorithm of isophases, the applicability of the theory is demonstrated by a signal of regular human respiration. For chaotic oscillations, generalized isophases can only be obtained up to a certain approximation. The intimate relationship between these approximate isophase, chaotic phase diffusion, and unstable periodic orbits is explained with the example of the chaotic \roes oscillator. Together, the concept of generalized isophases and the effective phase theory allow for a unified, and invariant phase description of stochastic and chaotic irregular oscillations. T2 - Phasendynamik irregulärer Oszillationen KW - Phasendynamik KW - Stochastische Oszillationen KW - Chaotische Oszillationen KW - Phasenkopplung KW - Zeitreihenanalyse KW - phase dynamics KW - stochastic oscillations KW - chaotic oscillations KW - phase coupling KW - time series analysis Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-50115 ER -