Predicting initiation and termination of atrial fibrillation from the ECG
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Dieter Hayn
Abstract
Atrial fibrillation is the most common cardiac arrhythmia, affecting more than two million people in the US. Several therapies for patients with atrial fibrillation are available, but methods to help physicians select the optimal therapy for an individual patient are still required. Knowledge of whether a patient with a normal ECG will exhibit atrial fibrillation in the future, as well as whether atrial fibrillation will terminate spontaneously, would be very useful in clinical routine. The paper presents a software system for predicting the initiation and termination of atrial fibrillation from the ECG. The algorithms have been validated on ECGs from several signal databases. Prediction of the initiation of atrial fibrillation was achieved by detecting premature heart beats and analyzing the morphology of their P waves. Prediction of the termination of atrial fibrillation was based on calculation of the major atrial frequency. This frequency has been shown to decrease significantly prior to the termination of atrial fibrillation. Nevertheless, the effect is much less distinct in the large data set used for this study compared to previous studies. The initiation of atrial fibrillation, however, could be correctly predicted in approximately 75% of the data analyzed.
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©2007 by Walter de Gruyter Berlin New York
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Articles in the same Issue
- Ralph Mueller and Herbert Witte join the Associate Editor team of Biomedizinische Technik/Biomedical Engineering
- Technological innovations in information engineering demand sustained updating and upgrading in biosignal processing applications: a continual renaissance
- Predicting initiation and termination of atrial fibrillation from the ECG
- Predicting the QRS complex and detecting small changes using principal component analysis
- The role of independent component analysis in the signal processing of ECG recordings
- Implantable cardioverter defibrillator algorithms: status review in terms of computational cost
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- Corrected body surface potential mapping
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- Autonomic cardiac control in animal models of cardiovascular diseases II. Variability analysis in transgenic rats with α-tropomyosin mutations Asp175Asn and Glu180Gly
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- Comparing a template approach and complex bandpass filtering for single-trial analysis of auditory evoked M100
- Wavelet-based analysis of MMN responses in children
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- EMG analysis of the thenar muscles as a model for EMG-triggered larynx stimulation
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