Literature DB >> 17472716

Understanding and interpreting dominant frequency analysis of AF electrograms.

Jason Ng1, Jeffrey J Goldberger.   

Abstract

Dominant frequency analysis of atrial electrograms has been used to understand the pathophysiology of atrial fibrillation (AF). Although dominant frequency is an effective tool to estimate activation rate during AF, other factors besides activation rate may alter the results. Therefore, an adequate conceptual understanding of frequency domain analysis is required to properly use this technique and interpret the results. This review, while avoiding the use of formulas and equations, aims to explain fundamental theory of how signals can be decomposed into sine waves and how these sine waves relate to the activation rate detected from the electrograms. Through a series of examples and illustrations this relationship can be easily conceptualized. This will in turn allow the strengths and limitations of dominant frequency analysis to be better understood and improve its applicability to potential clinical usages.

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Year:  2007        PMID: 17472716     DOI: 10.1111/j.1540-8167.2007.00832.x

Source DB:  PubMed          Journal:  J Cardiovasc Electrophysiol        ISSN: 1045-3873


  20 in total

1.  QRS subtraction for atrial electrograms: flat, linear and spline interpolations.

Authors:  A Ahmad; J L Salinet; P Brown; J H Tuan; P Stafford; G Andre Ng; F S Schlindwein
Journal:  Med Biol Eng Comput       Date:  2011-09-30       Impact factor: 2.602

Review 2.  Processing and analysis of cardiac optical mapping data obtained with potentiometric dyes.

Authors:  Jacob I Laughner; Fu Siong Ng; Matthew S Sulkin; R Martin Arthur; Igor R Efimov
Journal:  Am J Physiol Heart Circ Physiol       Date:  2012-07-20       Impact factor: 4.733

Review 3.  Mechanistic Approaches to Detect, Target, and Ablate the Drivers of Atrial Fibrillation.

Authors:  Jorge G Quintanilla; Julián Pérez-Villacastín; Nicasio Pérez-Castellano; Sandeep V Pandit; Omer Berenfeld; José Jalife; David Filgueiras-Rama
Journal:  Circ Arrhythm Electrophysiol       Date:  2016-01

Review 4.  Review of Dominant Frequency Analysis in Atrial Fibrillation.

Authors:  Rakesh Latchamsetty; Abraham G Kocheril
Journal:  J Atr Fibrillation       Date:  2009-10-01

5.  Comparison of filtering methods for extracellular gastric slow wave recordings.

Authors:  Niranchan Paskaranandavadivel; Gregory O'Grady; Peng Du; Leo K Cheng
Journal:  Neurogastroenterol Motil       Date:  2012-09-13       Impact factor: 3.598

6.  Comparison of spectral estimators for characterizing fractionated atrial electrograms.

Authors:  Edward J Ciaccio; Angelo B Biviano; Hasan Garan
Journal:  Biomed Eng Online       Date:  2013-07-16       Impact factor: 2.819

7.  Atrial electromechanical cycle length mapping in paced canine hearts in vivo.

Authors:  Alexandre Costet; Ethan Bunting; Julien Grondin; Alok Gambhir; Elisa E Konofagou
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2015-07       Impact factor: 2.725

8.  Spectral profiles of complex fractionated atrial electrograms are different in longstanding and acute onset atrial fibrillation atrial electrogram spectra.

Authors:  Edward J Ciaccio; Angelo B Biviano; William Whang; Alok Gambhir; Hasan Garan
Journal:  J Cardiovasc Electrophysiol       Date:  2012-05-11

9.  Ablation of complex fractionated atrial electrograms in catheter ablation for AF; where have we been and where are we going?

Authors:  Jane Caldwell; Damian Redfearn
Journal:  Curr Cardiol Rev       Date:  2012-11

10.  Benchmarking electrophysiological models of human atrial myocytes.

Authors:  Mathias Wilhelms; Hanne Hettmann; Mary M Maleckar; Jussi T Koivumäki; Olaf Dössel; Gunnar Seemann
Journal:  Front Physiol       Date:  2013-01-04       Impact factor: 4.566

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