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Comput Biol Med. 2018 Nov 1;102:315-326. doi: 10.1016/j.compbiomed.2018.07.008. Epub 2018 Jul 17.

Analytical approaches for myocardial fibrillation signals.

Author information

1
ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom.
2
Division of Imaging Sciences and Bioengineering, King's College London, United Kingdom.
3
ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom; Department of Aeronautics, Imperial College London, United Kingdom.
4
ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom. Electronic address: f.ng@imperial.ac.uk.

Abstract

Atrial and ventricular fibrillation are complex arrhythmias, and their underlying mechanisms remain widely debated and incompletely understood. This is partly because the electrical signals recorded during myocardial fibrillation are themselves complex and difficult to interpret with simple analytical tools. There are currently a number of analytical approaches to handle fibrillation data. Some of these techniques focus on mapping putative drivers of myocardial fibrillation, such as dominant frequency, organizational index, Shannon entropy and phase mapping. Other techniques focus on mapping the underlying myocardial substrate sustaining fibrillation, such as voltage mapping and complex fractionated electrogram mapping. In this review, we discuss these techniques, their application and their limitations, with reference to our experimental and clinical data. We also describe novel tools including a new algorithm to map microreentrant circuits sustaining fibrillation.

KEYWORDS:

Analysis; Atrial fibrillation; Complex fractionated electrograms; Dominant frequency; Organizational index; Phase analysis; Rotors; Shannon entropy; Ventricular fibrillation; Voltage mapping

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