DocumentCode :
3378354
Title :
Computers in cardiology/physionet challenge 2004: AF classification based on clinical features
Author :
Lemay, M. ; Ihara, Z. ; Vesin, J.M. ; Kappenberger, L.
fYear :
2004
fDate :
19-22 Sept. 2004
Firstpage :
669
Lastpage :
672
Abstract :
The Computers in Cardiology / Physionet Challenge 2004 deals with the classification of ECG signals from AF patients into three categories: types N, S and T corresponding to AF episodes terminating never; soon and immediately, respectively. In our study, diflerent features were used, extracted by the experienced clinician among the authors (LK) on the supplied training set. Algorithms were developped to quantify these features from provided ECG data. A Support Vector Muchine was used to classic these features. In this papel: we present our method, results and conclusion about this clinically-oriented approach.
Keywords :
Atrial fibrillation; Cardiology; Electrocardiography; Feature extraction; Pattern analysis; Signal processing; Support vector machine classification; Support vector machines; Testing; Time series analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers in Cardiology, 2004
Conference_Location :
Chicago, IL, USA
Print_ISBN :
0-7803-8927-1
Type :
conf
DOI :
10.1109/CIC.2004.1443027
Filename :
1443027
Link To Document :
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