Publication: A hierarchical algorithm for causality discovery among atrial fibrillation electrograms
Loading...
Identifiers
Publication date
2016-05-19
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Impact
Export
Abstract
Multi-channel intracardiac electrocardiograms (electrograms)
are sequentially acquired, at the electrophysiology laboratory,
in order to guide radio frequency catheter ablation during
heart surgery performed on patients with sustained atrial
fibrillation (AF). These electrograms are used by cardiologists
to determine candidate areas for ablation (e.g., areas
corresponding to high dominant frequencies or complex fractionated
electrograms). In this paper, we introduce a novel
hierarchical algorithm for causality discovery among these
multi-output sequentially acquired electrograms. The causal
model obtained provides important information about the
propagation of the electrical signals inside the heart, uncovering
wavefronts and activation patterns that will serve to
increase our knowledge about AF and guide cardiologists towards
candidate areas for catheter ablation. Numerical results
on synthetic signals, generated using the FitzHugh-Nagumo
model, show the good performance of the proposed approach.
Description
Proceeding of 2016 IEEE International Conference on Acoustics, Speech, and Signal Processing proceedings, March 20–25, 2016, Shanghai, China
Keywords
Standards, Electrocardiography, Atrial fibrillation, Granger causality, Radio frequency
Bibliographic citation
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) proceedings, March 20–25, 2016, Shanghai, China, pp.: 774-778. Piscataway, IEEE.