A new transform for the analysis of complex fractionated atrial electrograms
Open Access
- 1 January 2011
- journal article
- research article
- Published by Springer Science and Business Media LLC in BioMedical Engineering OnLine
- Vol. 10 (1), 35
- https://doi.org/10.1186/1475-925x-10-35
Abstract
Representation of independent biophysical sources using Fourier analysis can be inefficient because the basis is sinusoidal and general. When complex fractionated atrial electrograms (CFAE) are acquired during atrial fibrillation (AF), the electrogram morphology depends on the mix of distinct nonsinusoidal generators. Identification of these generators using efficient methods of representation and comparison would be useful for targeting catheter ablation sites to prevent arrhythmia reinduction. A data-driven basis and transform is described which utilizes the ensemble average of signal segments to identify and distinguish CFAE morphologic components and frequencies. Calculation of the dominant frequency (DF) of actual CFAE, and identification of simulated independent generator frequencies and morphologies embedded in CFAE, is done using a total of 216 recordings from 10 paroxysmal and 10 persistent AF patients. The transform is tested versus Fourier analysis to detect spectral components in the presence of phase noise and interference. Correspondence is shown between ensemble basis vectors of highest power and corresponding synthetic drivers embedded in CFAE. The ensemble basis is orthogonal, and efficient for representation of CFAE components as compared with Fourier analysis (p ≤ 0.002). When three synthetic drivers with additive phase noise and interference were decomposed, the top three peaks in the ensemble power spectrum corresponded to the driver frequencies more closely as compared with top Fourier power spectrum peaks (p ≤ 0.005). The synthesized drivers with phase noise and interference were extractable from their corresponding ensemble basis with a mean error of less than 10%. The new transform is able to efficiently identify CFAE features using DF calculation and by discerning morphologic differences. Unlike the Fourier transform method, it does not distort CFAE signals prior to analysis, and is relatively robust to jitter in periodic events. Thus the ensemble method can provide a useful alternative for quantitative characterization of CFAE during clinical study.Keywords
This publication has 35 references indexed in Scilit:
- Ablation of Long-Standing Persistent Atrial FibrillationJournal of Atrial Fibrillation, 2010
- New methods for estimating local electrical activation rate during atrial fibrillationHeart Rhythm, 2009
- Rotor meandering contributes to irregularity in electrograms during atrial fibrillationHeart Rhythm, 2008
- Quantifying fractionation and rate in human atrial fibrillation using monophasic action potentials: implications for substrate mappingEP Europace, 2007
- Using Electrocardiographic Activation Time and Diastolic Intervals to Separate Focal From Macro–Re-Entrant Atrial TachycardiasJournal of the American College of Cardiology, 2007
- Technical Considerations for Dominant Frequency AnalysisJournal of Cardiovascular Electrophysiology, 2007
- Understanding and Interpreting Dominant Frequency Analysis of AF ElectrogramsJournal of Cardiovascular Electrophysiology, 2007
- Evaluating Fluctuations in Human Atrial Fibrillatory Cycle Length Using Monophasic Action PotentialsPacing and Clinical Electrophysiology, 2006
- Standing Excitation Waves in the Heart Induced by Strong Alternating Electric FieldsPhysical Review Letters, 2001
- A technique for measurement of the extent of spatial organization of atrial activation during atrial fibrillation in the intact human heartIEEE Transactions on Biomedical Engineering, 1995