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

Drago Torkar, Pedro David Arini

2016

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

References

  1. Antzelevitch, C., Viskin, S., Shimizu, W., Yan, G., Kowey, P., Zhang, L., Sicouri, S., Di Diego, J., and Burashnikov, A. (2007). Does Tpeak-Tend provide an index of transmural dispersion of repolarization? Hearth Rhythm, 4(8):1114-1119.
  2. Arini, P. D., Bertrán, G. C., Valverde, E. R., and Laguna, P. (2008). T-wave width as an index for quantification of ventricular repolarization dispersion: Evaluation in an isolated rabbit heart model. Biomed. Signal Proc. Control, 3:67-77.
  3. Cai, B. and Jiang, X. (2014). A novel artificial neural network method for biomedical prediction based on matrix pseudo-inversion. J. of Biomed. Informatics, 48:114-121.
  4. Chen, F., Pan, Y., Li, K., Cheng, K., and Huan, R. (2015). Standard 12-lead ECG synthesis using a GA optimized BP neural network. 7th International Conference on Advanced Computational Intelligence, 7:289- 293.
  5. Di Diego, J. M., Sun, Z. Q., and Antzelevitch, C. (1996). Ito and action potential notch are smaller in left vs. right canine ventricular epicardium. A. J. Physiol., 271:H548.
  6. Dreiseitl, S. and Ohno-Machado, L. (2002). Logistic regression and artificial neural network classification models: a methodology review. J. of Biomed. Informatics, 35:352-359.
  7. Fuller, M. S., Sándor, G., Punske, B., Taccardi, B., MacLeod, R. S., Ershler, P. R., Green, L. S., and Lux, R. L. (2000). Estimates of repolarization and its dispersion from electrocardiographic measurements: direct epicardial assesment in the canine heart. J. of Electrocardiol., 33:171-180.
  8. Han, J. and Moe, G. K. (1964). Nonuniform recovery of excitability in ventricular muscle. Circ. Res., 14:44- 54.
  9. Horowitz, L., Spear, J., and Moore, E. (1981). Relation of endocardial and epicardial ventricular fibrillation thresholds of the right and left ventricles. Am. J. Cardiol., 48:698-701.
  10. Kuo, C. S., Atarashi, H., Reddy, P., and Suracwicz, B. (1985). Dispersion of ventricular repolarization and arrhythmia: Study of two consecutive ventricular premature complexes. Circ., 72:370-376.
  11. Kuo, C. S., Munakata, K., Reddy, P., and Surawicz, B. (1983). Characteristics and possible mechanism of ventricular arrhytmia dependent on the dispersion of action potential. Circ., 67:1356-1367.
  12. Laurita, K. R., Girouard, S. D., Fadi, G. A., and Rosenbaum, D. S. (1998). Modulated dispersion explains changes in arrhythmia vulnerability during premature stimulation of the heart. Circ., 98:2774-2780.
  13. Mendieta, J. G. (2012). Algoritmo para el delineado de sen˜ales ECG en un modelo animal empleando técnicas avanzadas de procesamiento de sen˜ales. Master Thesis. , Facultad de Ingeniería de la Universidad de Buenos Aires.
  14. Meyer, C. R. and Keiser, H. t. (1977). Electrocardiogram baseline noise estimation and removal using cubic spline and state-space computation techniques. Comp. and Biomed. Res., 10:459-470.
  15. Rosenbaum, D. S., Kaplan, D. T., Kanai, A., Jackson, L., Garan, H., Cohen, R. J., and Salama, G. (1991). Repolarization inhomogeneities in ventricular myocardium change dynamically with abrupt cycle length shortening. Circ., 84:1333-1345.
  16. Rosner, B. (1994). Fundamentals of Biostatistics. Duxbury Press, fourth edition edition.
  17. Shaikhina, T., Lowe, D., Daga, S., Briggs, D., Higgins, R., and Khovanova, N. (2015). Machine learning for predictive modelling based on small data in Biomedical Engineering. IFAC-PapersOnLine, 48:469-474.
  18. Shimizu, W. and Antzelevitch, C. (1998). Cellular basis for the ECG features of the LQT1 form of the long QT syndrome. efects of ß adrenergic agonist and antagonist and sodium channel blockers on transmural dispersion of repolarization and torsades de pointes. Circ., 98:2314-2322.
  19. Smetana, P., Schmidt, A., Zabel, M., Hnatkova, K., Franz, M., Huber, K., and Malik, M. (2011). Assessment of repolarization heterogeneity for prediction of mortality in cardiovascular disease: peak to the end of the T wave interval and nondipolar repolarization components. J Electrocardiol, 44:301-308.
  20. Spear, J. and Moore, E. (2000). Modulation of arrhytmias by isoproterenol in a rabbit heart model of dSotalol induced long QT intervals. American J. Physiol, (279):H15-H25.
  21. Surawicz, B. (1997). Ventricular fibrillation and dispersion of repolarization. J. Cardiovasc. Electrophysiol., 8:1009-1012.
  22. Noble, D. and Cohen, I. (1978). The interpretation of the T wave of the electrocardiogram. Cardiovasc. Res., 12:13-27.
  23. Yan, G. and Jack, M. (2003). Electrocardiographic T wave: A symbol of transmural dispersion of repolarization in the ventricles. J. of Cardiovasc. Electrophysiol., 14:639-640.
  24. Yuan, S., Blomström-Lundqvist, C., Pherson, C., Wohlfart, B., and Olsson, S. B. (1996). Dispersion of ventricular repolarization following double and triple programmed stimulation: A clinical study using the monophasic action potential recording technique. Eur. Heart J., 17:1080-1091.
  25. Zabel, M., Hohonloser, S. H., Beherens, S., Woosley, R. L., and Franz, M. R. (1997). Differential effects of dSotalol, quinidine and amiodarone on dispersion of ventricular repolarization in the isolated rabbit heart. J. Cardiovascular Electrophysiol., 8:1239-1245.
  26. Zabel, M., Portnoy, S., and Franz, M. R. (1995). Electrocardiographic indexes of dispersion of ventricular repolarization: An isolated heart validation study. J. Am. Coll. Cardiol., 25:746-752.
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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