Complex Dynamics in Physiological Systems: From Heart to by Louis M. Pecora, Linda Moniz, Jonathan Nichols, Thomas L. PDF

By Louis M. Pecora, Linda Moniz, Jonathan Nichols, Thomas L. Carroll (auth.), Syamal K. Dana, Prodyot K. Roy, Jürgen Kurths (eds.)

ISBN-10: 1402091427

ISBN-13: 9781402091421

Nonlinear dynamics has develop into a huge box of analysis in recent times in lots of components of the ordinary sciences. particularly, it has power purposes in biology and drugs; nonlinear facts research has helped to observe the growth of cardiac ailment, physiological problems, for instance episodes of epilepsy, and others. This e-book makes a speciality of the present traits of analysis in regards to the prediction of surprising cardiac dying and the onset of epileptic seizures, utilizing the nonlinear research in accordance with ECG and EEG information. themes coated contain the research of cardiac types and neural types. The publication is a suite of contemporary study papers by means of best physicists, mathematicians, cardiologists and neurobiologists who're actively desirous about utilizing the ideas of nonlinear dynamics to discover the practical behaviours of center and mind less than basic and pathological stipulations. This assortment is meant for college students in physics, arithmetic and clinical sciences, and researchers in interdisciplinary components of physics and biology.

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23. P. Grassberger and I. Procaccia, Characterisation of strange attractors, Phys. Rev. , 50, 346 (1983). 24. P. Grassberger and I. Procaccia, Measuring the strangeness of strange attractors, Physica D, 9, 189 (1983). 25. T. Schreiber and A. Schmitz, Improved surrogate data for nonlinearity tests, Phys. Rev. , 77, 635 (1996). 26. R. Hegger, H. Kantz and T. Schreiber, Practical implementation of Nonlinear time series methods: The TISEAN package, CHAOS, 9, 413 (1999). 27. C. H. P. Kadanof, I. I. Shraiman, Fractal measures and their singularities: The characterization of strange sets, Phys.

2006) Nonlinear parametric model for Granger causality of time series. Phys Rev E 73:066216. 46 T. Buchner et al. 4. Hoyer D, Frank B, Goetze C, et al. (2007) Interactions between short-term and long-term cardiovascular control mechanisms – a new aspect in risk stratification. Chaos 17:015110-1015110-8. 5. Schreiber T. (2000) Measuring information transfer. Phys. Rev. Lett. 85:461. 6. Romano Blasco MC. (2004) Synchronization analysis by means of recurrences in phase space. Dissertation, University of Potsdam.

A, 37, 1314 (1988). Direction of Information Flow Between Heart Rate, Blood Pressure and Breathing Teodor Buchner, Jan J. Zebrowski, Grzegorz Gielerak and Monika Grze¸da Abstract The problem of a reliable determination of the causal precedence of physiological signals with no a priori knowledge is addressed. Three physiologically important signals: blood pressure variability (BPV), heart rate variability (HRV) and breathing are taken as an example. Below we introduce a novel method of analysis of physiological signals based on local linear cross-correlation.

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Complex Dynamics in Physiological Systems: From Heart to Brain by Louis M. Pecora, Linda Moniz, Jonathan Nichols, Thomas L. Carroll (auth.), Syamal K. Dana, Prodyot K. Roy, Jürgen Kurths (eds.)


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