Abstract
Ventricular ectopic beats (VEBs) trigger a characteristic response of the heart called heart rate turbulence (HRT). The HRT can be used to predict sudden cardiac death in patients with a history of myocardial infarction. In this work, we present a reliable algorithm to detect and classify ectopic beats. Every electrocardiogram (ECG) is processed with innovative filtering techniques, artifact detection methods, and a robust multichannel analysis to produce accurate annotation results. For the classification task, a support vector machine was used. Furthermore, a new approach to the analysis of HRT is proposed. The HRT is interpreted as the response of a second-order system to an external perturbation. The system theoretical parameters were estimated. The influence of VEB on the morphology of subsequent T waves was also analyzed. A strong influence was detected in the study with 14 patients experiencing frequent VEB. The evolution of the morphology of the T wave with every new beat was studied, and it could be concluded that an exponential shape underlies this dynamic process and was called morphological heart rate turbulence (MHRT). Parameters were defined to quantify the MHRT. The analysis of the MHRT could help to understand the influence of an ectopic beat on the repolarization processes of the heart and more accurately stratify the risk of sudden cardiac death.
The authors would like to thank the German state of Baden-Württemberg for the financial support provided over the last years. The authors would also like to thank Prof. Dr. rer. nat. Wilhelm Stork and his research group at the Institute for Information Processing Technologies at the Karlsruhe Institute of Technology for providing one of the ECG signals analyzed in this work.
References
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Articles in the same Issue
- Masthead
- Masthead
- Editorial
- Young scientist award papers from the workshop on bioelectric and biomagnetic signal processing 2012
- Research articles
- Ectopic beats and their influence on the morphology of subsequent waves in the electrocardiogram
- Online learning algorithms for principal component analysis applied on single-lead ECGs
- Coupling analysis of transient cardiovascular dynamics
- Multiple circular-circular correlation coefficients for the quantification of phase synchronization processes in the brain
- Validity of subthalamic-cortical coherency observed in patients with Parkinson’s disease
- Identifying causal networks of neuronal sources from EEG/MEG data with the phase slope index: a simulation study
- QRS complex duration enhancement as ventricular late potential indicator by signal-averaged ECG using time-amplitude alignments
- Are there any differences in various polyaxial locking systems? A mechanical study of different locking screws in multidirectional angular stable distal radius plates
- Integrating strength tests of amputees within the protocol of conventional clinical gait analysis: a novel approach
- Simultaneous assessment of autonomic nervous and vascular endothelial functions in a rat model