Information Theory and Atrial Fibrillation (AF): A Review

Atrial Fibrillation (AF) is the most common cardiac rhythm disorder seen in hospitals and in general practice, accounting for up to a third of arrhythmia related hospitalizations. Unfortunately, AF treatment is in practice complicated by the lack of understanding of the fundamental mechanisms underl...

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Published inFrontiers in physiology Vol. 9; p. 957
Main Authors Dharmaprani, Dhani, Dykes, Lukah, McGavigan, Andrew D, Kuklik, Pawel, Pope, Kenneth, Ganesan, Anand N
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 18.07.2018
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Summary:Atrial Fibrillation (AF) is the most common cardiac rhythm disorder seen in hospitals and in general practice, accounting for up to a third of arrhythmia related hospitalizations. Unfortunately, AF treatment is in practice complicated by the lack of understanding of the fundamental mechanisms underlying the arrhythmia, which makes detection of effective ablation targets particularly difficult. Various approaches to AF mapping have been explored in the hopes of better pinpointing these effective targets, such as Dominant Frequency (DF) analysis, complex fractionated electrograms (CFAE) and unipolar reconstruction (FIRM), but many of these methods have produced conflicting results or require further investigation. Exploration of AF using information theoretic-based approaches may have the potential to provide new insights into the complex system dynamics of AF, whilst also providing the benefit of being less reliant on empirically derived definitions in comparison to alternate mapping approaches. This work provides an overview of information theory and reviews its applications in AF analysis, with particular focus on AF mapping. The works discussed in this review demonstrate how understanding AF from a signal property perspective can provide new insights into the arrhythmic phenomena, which may have valuable clinical implications for AF mapping and ablation in the future.
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Reviewed by: Luca Faes, Università degli Studi di Palermo, Italy; Richard Gray, State Food and Drug Administration, China
Edited by: Ahsan H. Khandoker, Khalifa University, United Arab Emirates
This article was submitted to Computational Physiology and Medicine, a section of the journal Frontiers in Physiology
ISSN:1664-042X
1664-042X
DOI:10.3389/fphys.2018.00957