Phase coupling in the cardiorespiratory interaction.

Markovian analysis is applied to derive nonlinear stochastic equations for the reconstruction of heart rate and respiration rate variability data. A model of their 'phase' interactions is obtained for the first time, thereby gaining new insights into the strength and direction of the cardiorespiratory phase coupling. The reconstructed model can reproduce synchronisation phenomena between the cardiac and the respiratory systems, including switches in synchronisation ratio. The technique is equally applicable to the extraction of the multi-dimensional couplings between many interacting subsystems.

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

[2]  M. Rosenblum,et al.  Identification of coupling direction: application to cardiorespiratory interaction. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  Muhammad Sahimi,et al.  New computational approaches to the analysis of interbeat intervals in human subjects , 2006, Computing in Science & Engineering.

[4]  H. Risken Fokker-Planck Equation , 1984 .

[5]  A Stefanovska,et al.  Nonlinear statistical modeling and model discovery for cardiorespiratory data. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[6]  Kurths,et al.  Phase synchronization of chaotic oscillators. , 1996, Physical review letters.

[7]  K. Chon,et al.  al-Input Nonlinear System Analysis ic Modulation of Heart Rate , 1996 .

[8]  D. Eckberg,et al.  The human respiratory gate. , 2003, The Journal of physiology.

[9]  Jürgen Kurths,et al.  Synchronization - A Universal Concept in Nonlinear Sciences , 2001, Cambridge Nonlinear Science Series.

[10]  D. T. Kaplan,et al.  Nonlinear interactions between respiration and heart rate: classical physiology or entrained nonlinear oscillators , 1988, Proceedings. Computers in Cardiology 1988.

[11]  Aneta Stefanovska,et al.  Synchronization and modulation in the human cardiorespiratory system , 2000 .

[12]  M. Paluš,et al.  Interactions between cardiac, respiratory and EEG‐δ oscillations in rats during anaesthesia , 2007 .

[13]  J. Kurths,et al.  Phase synchronization: from theory to data analysis , 2003 .

[14]  A Stefanovska,et al.  Inference of a nonlinear stochastic model of the cardiorespiratory interaction. , 2005, Physical review letters.

[15]  Jürgen Kurths,et al.  Synchronization: Phase locking and frequency entrainment , 2001 .

[16]  T D Frank,et al.  Noise-covered drift bifurcation of dissipative solitons in a planar gas-discharge system. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  A Stefanovska,et al.  Incipient cardiovascular autonomic imbalance revealed by wavelet analysis of heart rate variability in Type 2 diabetic patients , 2007, Diabetic medicine : a journal of the British Diabetic Association.

[18]  Gradisek,et al.  Analysis of time series from stochastic processes , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[19]  J. Peinke,et al.  Description of a Turbulent Cascade by a Fokker-Planck Equation , 1997 .

[20]  A. Stefanovska,et al.  Wavelet analysis of oscillations in the peripheral blood circulation measured by laser Doppler technique , 1999, IEEE Transactions on Biomedical Engineering.

[21]  A. Winfree The geometry of biological time , 1991 .

[22]  Ward Edwards,et al.  Bayesian statistical inference for psychological research. , 1963 .

[23]  A G Balanov,et al.  Phase synchronization between several interacting processes from univariate data. , 2001, Physical review letters.

[24]  M Reza Rahimi Tabar,et al.  Stochastic analysis and regeneration of rough surfaces. , 2003, Physical review letters.

[25]  Aneta Stefanovska,et al.  Physics of the human cardiovascular system , 1999 .

[26]  Khadija Iqbal,et al.  An introduction , 1996, Neurobiology of Aging.

[27]  H. Risken The Fokker-Planck equation : methods of solution and applications , 1985 .

[28]  Thorsten Ackemann,et al.  Parametric Data Analysis of Bistable Stochastic Systems , 2005 .

[29]  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.

[30]  M. Rosenblum,et al.  Chapter 9 Phase synchronization: From theory to data analysis , 2001 .

[31]  Janez Jam,et al.  Nonlinear cardio-respiratory interactions revealed by time-phase bispectral analysis , 2004 .

[32]  Aneta Stefanovska,et al.  Nonlinear cardio-respiratory interactions revealed by time-phase bispectral analysis. , 2004, Physics in medicine and biology.

[33]  A Stefanovska,et al.  Reversible transitions between synchronization states of the cardiorespiratory system. , 2000, Physical review letters.

[34]  M. Besserve,et al.  Towards a proper estimation of phase synchronization from time series , 2006, Journal of Neuroscience Methods.

[35]  J. Kurths,et al.  Heartbeat synchronized with ventilation , 1998, Nature.

[36]  J. Kurths,et al.  Phase Synchronization of Chaotic Oscillators by External Driving , 1997 .

[37]  R. Friedrich,et al.  Analysis of data sets of stochastic systems , 1998 .

[38]  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 .

[39]  A. Stefanovska,et al.  Low-frequency oscillations of the laser Doppler perfusion signal in human skin. , 2006, Microvascular research.

[40]  Jürgen Kurths,et al.  Detection of n:m Phase Locking from Noisy Data: Application to Magnetoencephalography , 1998 .

[41]  Friedrich,et al.  How to quantify deterministic and random influences on the statistics of the foreign exchange market , 1999, Physical review letters.

[42]  Hermann Haken,et al.  Synergetics: An Introduction , 1983 .