DocumentCode
3374892
Title
Automated prediction of spontaneous termination of atrial fibrillation from electrocardiograms
Author
Hayn, D. ; Edegger, K. ; Scherr, D. ; Lercher, P. ; Rotman, B. ; Klein, W. ; Schreier, G.
Author_Institution
Biosignal Process. & Telemedicine, ARC Seibersdorf Res. GmbH, Graz, Austria
fYear
2004
fDate
19-22 Sept. 2004
Firstpage
117
Lastpage
120
Abstract
An algorithm for differentiating ECGs with atrial fibrillation (AF) that will spontaneously terminate within 60 seconds from signals, where it won´t, has been developed using the AF termination challenge database from physionet. The algorithm was based on the calculation of the major AF frequency by canceling out the QRS complexes and T waves from the original ECGs and then applying short time Fourier transform techniques to the remaining signals. The major AF frequency and the mean RR interval were considered for classification. Validation of the algorithm was done by sending the algorithm´s results for test-set-a of the AF termination challenge database to physionet. We found, that for ECGs with a low AF frequency it was more likely, that AF would terminate spontaneously than for ECGs with higher frequencies. Our algorithm was able to correctly classify 93.3% (28/30) of the signals of the test-set-a.
Keywords
Fourier transforms; blood vessels; diseases; electrocardiography; medical signal processing; signal classification; 60 s; ECG; Fourier transform technique; QRS complex; RR interval; T wave; atrial fibrillation frequency; automated prediction; electrocardiogram; physionet; spontaneous termination; termination challenge database; Atrial fibrillation; Cardiology; Drugs; Electrocardiography; Fourier transforms; Frequency; Signal processing; Spatial databases; Telemedicine; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computers in Cardiology, 2004
Print_ISBN
0-7803-8927-1
Type
conf
DOI
10.1109/CIC.2004.1442885
Filename
1442885
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