Literature DB >> 2456540

Computer discrimination of atrial fibrillation and regular atrial rhythms from intra-atrial electrograms.

J Slocum1, A Sahakian, S Swiryn.   

Abstract

Reliable detection of atrial fibrillation from intra-atrial data is an important requirement for automatic implantable anti-tachycardia devices. Simultaneous filtered and unfiltered intra-atrial electrograms were recorded from patients in regular rhythms (12 sinus rhythms and six regular atrial tachycardias) and atrial fibrillation (nine rhythms). Each rhythm was broken down into consecutive 4-second data segments for analysis by atrial rate calculation, power spectrum analysis and amplitude probability density function generation. Significant differences were found between regular rhythms and atrial fibrillation for atrial rate, for the percentage of the total power in the 4-9 hertz band and for amplitude probability density close to the isoelectric region. There was no overlap for any of these three parameters. For each method of analysis, algorithms were generated to discriminate individual data segments from regular rhythms and atrial fibrillation with high sensitivity and specificity. Comparable results were found when sinus rhythm was excluded from the analysis. Characteristics of intra-atrial recordings during atrial fibrillation were remarkably similar to previously published reports of intra-ventricular recordings during ventricular fibrillation. Each of the three methods of analysis may provide an algorithm for accurate detection of atrial fibrillation by anti-tachycardia devices.

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Year:  1988        PMID: 2456540     DOI: 10.1111/j.1540-8159.1988.tb04557.x

Source DB:  PubMed          Journal:  Pacing Clin Electrophysiol        ISSN: 0147-8389            Impact factor:   1.976


  4 in total

Review 1.  Current approaches and future developments in automatic tachycardia detection and diagnosis.

Authors:  P S Astridge; G C Kaye; E J Perrins
Journal:  Br Heart J       Date:  1993-08

2.  Adaptive filters for analysis of intra-cardiac signals.

Authors:  N V Thakor
Journal:  Med Biol Eng Comput       Date:  1994-07       Impact factor: 2.602

Review 3.  Experimental and clinical AF mechanisms: bridging the divide.

Authors:  José Jalife
Journal:  J Interv Card Electrophysiol       Date:  2003-10       Impact factor: 1.900

4.  Atrial fibrillation organization: quantification of propofol effects.

Authors:  Raquel Cervigón; Javier Moreno; César Sánchez; Richard B Reilly; Julián Villacastín; José Millet; Francisco Castells
Journal:  Med Biol Eng Comput       Date:  2008-11-19       Impact factor: 2.602

  4 in total

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