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Content Provider | IEEE Xplore Digital Library |
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Author | Rieta, J.J. Hornero, F. Alcaraz, R. Moratal, D. |
Copyright Year | 2007 |
Description | Author affiliation: Valencia Univ. of Technol., Gandia (Rieta, J.J.) |
Abstract | Atrial tachyarrhythmias are a very common cardiovascular disease in clinical practice with an incidence that doubles with each advancing decade. A key issue to understand their pathophysiological mechanisms is the analysis and interpretation of atrial electrograms (AEG). To properly study these signals, ventricular artifacts have to be removed from the AEG. In this work, a new application of independent component analysis (ICA) to the AEG is presented where ventricular artifacts are removed from atrial recordings making use of only one reference lead. Therefore the technique is suitable when multi-lead recordings are unavailable as in atrial implantable cardioverter-defibrilators. The methodology has been compared with traditional techniques on a database of 20 patients. Performance was evaluated through atrial waveform similarity (S) and ventricular activity reduction (VDR) as a function of atrial rhythm regularity on a beat-by-beat basis. When the atrial tachyarrhythmia is quite regular, results show that ICA preserves the atrial waveform better than the other methods (median S=99.64%) whereas maintaining ventricular reduction (median VDR=6.32 dB). |
Starting Page | 6503 |
Ending Page | 6506 |
File Size | 603408 |
Page Count | 4 |
File Format | |
ISBN | 9781424407873 |
ISSN | 1557170X |
DOI | 10.1109/IEMBS.2007.4353849 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-08-22 |
Publisher Place | France |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Independent component analysis Low pass filters Rhythm Cardiovascular diseases Cardiology Disk recording Surgery Surface morphology Frequency Source separation |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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