ArticleFrontiers in physiology2018
Real-Time Rotational Activity Detection in Atrial Fibrillation.
Article in Frontiers in physiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- AI-Powered Precision: Revolutionizing Atrial Fibrillation Detection with Electrocardiograms.Journal of clinical medicine · 2025Review
- Atrial fibrillation driver identification through regional mutual information networks: a modeling perspective.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2022Article
- 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
- Convolutional Neural Networks for Mechanistic Driver Detection in Atrial Fibrillation.International journal of molecular sciences · 2022Article
- Structural Remodeling and Rotational Activity in Persistent/Long-Lasting Atrial Fibrillation: Gender-Effect Differences and Impact on Post-ablation Outcome.Frontiers in cardiovascular medicine · 2022Article
- Application of artificial intelligence ensemble learning model in early prediction of atrial fibrillation.BMC bioinformatics · 2021Article
- OpenEP: A Cross-Platform Electroanatomic Mapping Data Format and Analysis Platform for Electrophysiology Research.Frontiers in physiology · 2021Article
- Dynamic Local Activation Time Mapping in Heavily Scarred Left Atrium and Persistent Atrial Fibrillation: A proof of concept case report.Journal of atrial fibrillation · 2020Article
- Early Detection of Atrial Fibrillation Based on ECG Signals.Bioengineering (Basel, Switzerland) · 2020Article
- Real-Time Ventricular Cancellation in Unipolar Atrial Fibrillation Electrograms.Frontiers in bioengineering and biotechnology · 2020Article
- Standardizing Single-Frame Phase Singularity Identification Algorithms and Parameters in Phase Mapping During Human Atrial Fibrillation.Frontiers in physiology · 2020Article
- Addressing challenges of quantitative methodologies and event interpretation in the study of atrial fibrillation.Computer methods and programs in biomedicine · 2019Review
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rotational activations, or spiral waves, are one of the proposed mechanisms for atrial fibrillation (AF) maintenance. We present a system for assessing the presence of rotational activity from intracardiac electrograms (EGMs). Our system is able to operate in real-time with multi-electrode catheters of different topologies in contact with the atrial wall, and it is based on new local activation time (LAT) estimation and rotational activity detection methods. The EGM LAT estimation method is based on the identification of the highest sustained negative slope of unipolar signals. The method is implemented as a linear filter whose output is interpolated on a regular grid to match any catheter topology. Its operation is illustrated on selected signals and compared to the classical Hilbert-Transform-based phase analysis. After the estimation of the LAT on the regular grid, the detection of rotational activity in the atrium is done by a novel method based on the optical flow of the wavefront dynamics, and a rotation pattern match. The methods have been validated using
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