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Computer Discrimination of Atrial Fibrillation and Regular Atrial Rhythms from Intra-Atrial Electrograms
Authors:JANET SLOCUM  ALAN SAHAKIAN  STEVEN SWIRYN
Affiliation:Department of Electrical Engineering, Northwestern University, Evanston, IL.
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.
Keywords:intracardiac recordings    antitachycardia device    electrograms    spectrum    atrial fibrillation    arrhythmia
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