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

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

Applied Mathematics and Computation, 2022, vol. 425, issue C

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.

Keywords: Atrial fibrillation; Rotors; Electrograms signal processing; Fractional entropy; Scientific computing (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:425:y:2022:i:c:s0096300322001618

DOI: 10.1016/j.amc.2022.127077

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