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Fractional generalization of entropy improves the characterization of rotors in simulated atrial fibrillation

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  • Ugarte, Juan P.
  • Tenreiro Machado, J.A.
  • Tobón, Catalina

Abstract

Atrial fibrillation (AF) underlies disordered spatiotemporal electrical activity, that increases in complexity with the persistence of the arrhythmia. It has been hypothesized that a specific arrhythmogenic mechanism, known as rotor, is the main driver sustaining the AF. Thus, the ablation of rotors has been suggested as a therapeutic strategy to terminate the arrhythmia. Nonetheless, such strategy poses a problem related with the characterization of the rotor propagating activity. This work addresses the rotor characterization by means of a fractional generalization of the entropy concept. By adopting complex order derivative operators, we endorse the definition of information content. The derived metric is used to study the AF propagation dynamics in computational models. The results evince that the fractional entropy approach yields a better spatio-temporal characterization of rotor dynamics than the conventional entropy analysis, under a wide range of simulated fibrillation conditions.

Suggested Citation

  • Ugarte, Juan P. & Tenreiro Machado, J.A. & Tobón, Catalina, 2022. "Fractional generalization of entropy improves the characterization of rotors in simulated atrial fibrillation," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    • Handle: RePEc:eee:apmaco:v:425:y:2022:i:c:s0096300322001618
    DOI: 10.1016/j.amc.2022.127077
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    References listed on IDEAS

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    1. António Dinis F. Santos & Duarte Valério & J. A. Tenreiro Machado & António M. Lopes, 2019. "A fractional perspective to the modelling of Lisbon’s public transportation network," Transportation, Springer, vol. 46(5), pages 1893-1913, October.
    2. Zhang, Yongping & Shang, Pengjian & Xiong, Hui, 2019. "Multivariate generalized information entropy of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1212-1223.
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    Cited by:

    1. Ugarte, Juan P. & Gómez-Echavarría, Alejandro & Tobón, Catalina, 2023. "Optimal compactness of fractional Fourier domain characterizes frequency modulated signals," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

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