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Ann Biomed Eng. 2017 Apr;45(4):910-923. doi: 10.1007/s10439-016-1766-4. Epub 2016 Dec 5.

Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation.

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Department of Bioengineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, F-33600, Pessac-Bordeaux, France.
Department of Aeronautics, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
National Heart and Lung Institute, Imperial College London, 4th floor Imperial Centre for Translational and Experimental Medicine, Hammersmith Campus, Du Cane Road, London, W12 0NN, UK.


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 2 = 0.79) and propagation maps (median correlation 0.73) were measured using either unipolar or bipolar recordings. The algorithm is robust, uses standard signal processing techniques, and accurately quantifies AF wavefronts and sources. Identifying critical sources, such as rotors, in AF, may allow for more accurate targeting of ablation therapy and improved patient outcomes.


Cardiac arrhythmia; Electrogram analysis; Phase singularity mapping

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