Analysis of an Electrocardiographic Multilead System by Means of Artificial Neural Networks - Study of Repolarization During Premature Ventricular Stimulation

Drago Torkar, Pedro David Arini

Abstract

The ventricular repolarization dispersion (VRD) has been shown to increase with premature stimulation. Moreover, several differences between left ventricular and right ventricular, such as the anatomic properties and fibrillation threshold have been reported. However, few data exist regarding the influence of the site of stimulation on modulation of VRD measure by electrocardiographic. In the present work, several ECG indices of VRD, as a function of the coupling interval and the site of stimulation, were studied in an isolated heart rabbit preparation (n=18), using ECG multilead (5 rows x 8 columns) system with Artificial Neural Networks. In both ventricles, results have shown significant decreases in early repolarization duration, while in the left ventricle we have found significant increases of transmural dispersion. Also, we have observed that when the premature stimuli were applied to the left ventricle, the ventricular repolarization dispersion changes were detected using only one preferential electrode (row1-column3). When stimuli were elicited at the right ventricle, changes of VRD were detected by three electrodes (row3-column1, row2-column1 and row3-column8). Finally, a different ventricular repolarization dispersion was found as a function of the site of stimulatio

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Paper Citation


in Harvard Style

Torkar D. and Arini P. (2016). Analysis of an Electrocardiographic Multilead System by Means of Artificial Neural Networks - Study of Repolarization During Premature Ventricular Stimulation . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 34-41. DOI: 10.5220/0005663200340041


in Bibtex Style

@conference{biosignals16,
author={Drago Torkar and Pedro David Arini},
title={Analysis of an Electrocardiographic Multilead System by Means of Artificial Neural Networks - Study of Repolarization During Premature Ventricular Stimulation},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2016)},
year={2016},
pages={34-41},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005663200340041},
isbn={978-989-758-170-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2016)
TI - Analysis of an Electrocardiographic Multilead System by Means of Artificial Neural Networks - Study of Repolarization During Premature Ventricular Stimulation
SN - 978-989-758-170-0
AU - Torkar D.
AU - Arini P.
PY - 2016
SP - 34
EP - 41
DO - 10.5220/0005663200340041