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Estimation of Instantaneous Complex Dynamics through Lyapunov Exponents: A Study on Heartbeat Dynamics

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  • Gaetano Valenza
  • Luca Citi
  • Riccardo Barbieri

Abstract

Measures of nonlinearity and complexity, and in particular the study of Lyapunov exponents, have been increasingly used to characterize dynamical properties of a wide range of biological nonlinear systems, including cardiovascular control. In this work, we present a novel methodology able to effectively estimate the Lyapunov spectrum of a series of stochastic events in an instantaneous fashion. The paradigm relies on a novel point-process high-order nonlinear model of the event series dynamics. The long-term information is taken into account by expanding the linear, quadratic, and cubic Wiener-Volterra kernels with the orthonormal Laguerre basis functions. Applications to synthetic data such as the Hénon map and Rössler attractor, as well as two experimental heartbeat interval datasets (i.e., healthy subjects undergoing postural changes and patients with severe cardiac heart failure), focus on estimation and tracking of the Instantaneous Dominant Lyapunov Exponent (IDLE). The novel cardiovascular assessment demonstrates that our method is able to effectively and instantaneously track the nonlinear autonomic control dynamics, allowing for complexity variability estimations.

Suggested Citation

  • Gaetano Valenza & Luca Citi & Riccardo Barbieri, 2014. "Estimation of Instantaneous Complex Dynamics through Lyapunov Exponents: A Study on Heartbeat Dynamics," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-17, August.
  • Handle: RePEc:plo:pone00:0105622
    DOI: 10.1371/journal.pone.0105622
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    References listed on IDEAS

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    1. Leon Glass, 2001. "Synchronization and rhythmic processes in physiology," Nature, Nature, vol. 410(6825), pages 277-284, March.
    2. Chi-Sang Poon & Christopher K. Merrill, 1997. "Decrease of cardiac chaos in congestive heart failure," Nature, Nature, vol. 389(6650), pages 492-495, October.
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    Cited by:

    1. Wang, Ping & Gu, Changgui & Yang, Huijie & Wang, Haiying & Moore, Jack Murdoch, 2023. "Characterizing systems by multi-scale structural complexity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    2. Campi, Gaetano & Bianconi, Antonio, 2022. "Periodic recurrent waves of Covid-19 epidemics and vaccination campaign," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).

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