Titlebook: Complexity and Nonlinearity in Cardiovascular Signals; Riccardo Barbieri,Enzo Pasquale Scilingo,Gaetano V Book 2017 Springer International

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Kechuan Wu,Xiaoping Wang,Mian Liditions, and thus providing additional prognostic information. In this chapter prominent complexity methods of non-linear dynamics as symbolic dynamics, Poincaré plot analyses, and compression entropy are introduced and their algorithmic implementations and application examples in clinical trials ar

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Lecture Notes in Computer Scienceo decompose the entropy of an assigned target system into components reflecting the information stored in the system and the information transferred to it from the other systems, as well as the nature (synergistic or redundant) of the information transferred to the target. The decomposition leads to

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Chi Li,Yisha Liu,Fei Yan,Yan Zhuangropy measures is it enables quantification of nonlinear dynamics underlying physiological processes over multiple time scales. The basic idea of multiscale entropy was initially developed in 2002 and has since witnessed considerable progress in methodological expansions along with growing applicatio

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Mária Marko?ová,Liz Franz,?ubica Beňu?kováoperties in a wide range of biological nonlinear systems, including cardiovascular control. In this chapter, we present recent methodological advances allowing to effectively estimate instantaneous approximate and sample entropy measures, as well as the instantaneous Lyapunov spectrum of a series of

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New Neuron Model for Blind Source Separationinternal and external perturbations. The assessment of changes in cardiovascular signals and in their interactions provides valuable information regarding the cardiovascular function. Time-frequency analysis is a useful tool to study the time-varying nature of the cardiovascular system because it pr

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