ArticleAnnals of biomedical engineering2017
Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation.
Article in Annals of biomedical engineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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The trial behind it
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Who cites it
21 citing papers in PubMed.
- Automated generation of ablation lesion masks: a unison of electro and optic flow mapping for persistent AF virtual cohorts.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026Article
- Directed Graph Mapping exceeds Phase Mapping for the detection of simulated 2D meandering rotors in fibrotic tissue with added noise.Computers in biology and medicine · 2024Article
- A computational modeling framework for pre-clinical evaluation of cardiac mapping systems.Frontiers in physiology · 2023Article
- Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate.Medical & biological engineering & computing · 2022Review
- DG-Mapping: a novel software package for the analysis of any type of reentry and focal activation of simulated, experimental or clinical data of cardiac arrhythmia.Medical & biological engineering & computing · 2022Article
- Critical appraisal of technologies to assess electrical activity during atrial fibrillation: a position paper from the European Heart Rhythm Association and European Society of Cardiology Working Group on eCardiology in collaboration with the Heart Rhythm Society, Asia Pacific Heart Rhythm Society, Latin American Heart Rhythm Society and Computing in Cardiology.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2022Article
- Computational models of atrial fibrillation: achievements, challenges, and perspectives for improving clinical care.Cardiovascular research · 2021Review
- Computational Analysis of Mapping Catheter Geometry and Contact Quality Effects on Rotor Detection in Atrial Fibrillation.Frontiers in physiology · 2021Article
- A Divergence-Based Approach for the Identification of Atrial Fibrillation Focal Drivers From Multipolar Mapping: A Computational Study.Frontiers in physiology · 2021Article
- Time-Averaged Wavefront Analysis Demonstrates Preferential Pathways of Atrial Fibrillation, Predicting Pulmonary Vein Isolation Acute Response.Frontiers in physiology · 2021Article
- Granger Causality-Based Analysis for Classification of Fibrillation Mechanisms and Localization of Rotational Drivers.Circulation. Arrhythmia and electrophysiology · 2020Article
- Challenges Associated with Interpreting Mechanisms of AF.Arrhythmia & electrophysiology review · 2020Review
- Standardised Framework for Quantitative Analysis of Fibrillation Dynamics.Scientific reports · 2019Article
- Addressing challenges of quantitative methodologies and event interpretation in the study of atrial fibrillation.Computer methods and programs in biomedicine · 2019Review
- Locating Atrial Fibrillation Rotor and Focal Sources Using Iterative Navigation of Multipole Diagnostic Catheters.Cardiovascular engineering and technology · 2019Article
- Iterative navigation of multipole diagnostic catheters to locate repeating-pattern atrial fibrillation drivers.Journal of cardiovascular electrophysiology · 2019Article
- ElectroMap: High-throughput open-source software for analysis and mapping of cardiac electrophysiology.Scientific reports · 2019Article
- Analytical approaches for myocardial fibrillation signals.Computers in biology and medicine · 2018Review
- Rotors Detected by Phase Analysis of Filtered, Epicardial Atrial Fibrillation Electrograms Colocalize With Regions of Conduction Block.Circulation. Arrhythmia and electrophysiology · 2018Article
- Interpreting Activation Mapping of Atrial Fibrillation: A Hybrid Computational/Physiological Study.Annals of biomedical engineering · 2018Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Extracellular electrograms recorded during atrial fibrillation (AF) are challenging to interpret due to the inherent beat-to-beat variability in amplitude and duration. Phase mapping represents these voltage signals in terms of relative position within the cycle, and has been widely applied to action potential and unipolar electrogram data of myocardial fibrillation. To date, however, it has not been applied to bipolar recordings, which are commonly acquired clinically. The purpose of this study is to present a novel algorithm for calculating phase from both unipolar and bipolar electrograms recorded during AF. A sequence of signal filters and processing steps are used to calculate phase from simulated, experimental, and clinical, unipolar and bipolar electrograms. The algorithm is validated against action potential phase using simulated data (trajectory centre error <0.8 mm); between experimental multi-electrode array unipolar and bipolar phase; and for wavefront identification in clinical atrial tachycardia. For clinical AF, similar rotational content (R
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