Jump to ContentJump to Main Navigation
Show Summary Details

Biomedical Engineering / Biomedizinische Technik

Editor-in-Chief: Dössel, Olaf

Editorial Board Member: Augat, Peter / Haueisen, Jens / Jockenhoevel, Stefan / Lenarz, Thomas / Leonhardt, Steffen / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Schmitz, Georg / Stieglitz, Thomas / Witte, Herbert / Boenick, Ulrich / Jaramaz, Branislav / Kraft, Marc / Lenthe, Harry / Lo, Benny / Mainardi, Luca / Micera, Silvestro / Penzel, Thomas / Robitzki, Andrea A. / Schaeffter, Tobias / Snedeker, Jess G. / Sörnmo, Leif / Sugano, Nobuhiko / Werner, Jürgen / Wintermantel, Erich /

6 Issues per year


IMPACT FACTOR increased in 2015: 1.650

Online
ISSN
1862-278X
See all formats and pricing
Volume 58, Issue 2 (Apr 2013)

Issues

Volume 57 (2012)

Ectopic beats and their influence on the morphology of subsequent waves in the electrocardiogram

Gustavo Lenis
  • Corresponding author
  • Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Kaiserstrasse 12, 76131 Karlsruhe, Germany
  • Email:
/ Tobias Baas
  • Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Kaiserstrasse 12, 76131 Karlsruhe, Germany
/ Olaf Dössel
  • Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Kaiserstrasse 12, 76131 Karlsruhe, Germany
Published Online: 2013-02-14 | DOI: https://doi.org/10.1515/bmt-2012-0114

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.

Keywords: electrocardiogram; heart rate turbulence; repolarization of ventricles; systems theory; T-wave morphology; ventricular ectopic beat

References

  • [1]

    Anthony Gomes J, Winters SL, Stewart D, Horowitz S, Milner M, Barreca P. A new noninvasive index to predict sustained ventricular tachycardia and sudden death in the first year after myocardial infarction: based on signal-averaged electrocardiogram, radionuclide ejection fraction and Holter monitoring. J Am Coll Cardiol 1987; 10: 349–357. [Crossref]

  • [2]

    Arya A, Haghjoo M, Ali Sadr-Ameli M. Risk stratification for arrhythmic death after myocardial infarction: current perspective and future direction. Int J Cardiol 2006; 108: 155–164. [PubMed] [Crossref]

  • [3]

    Baas T. ECG based analysis of the ventricular repolarisation in the human heart. PhD thesis. Karlsruhe: Karlsruhe Institute of Technology 2012.

  • [4]

    Baas T, Grafe K, Khawaja A, Dossel O. Investigation of parameters highlighting drug induced small changes of the T-wave’s morphology for drug safety studies. In: Engineering in Medicine and Biology Society, EMBC 2011 Annual International Conference of the IEEE. Piscataway, NJ, USA IEEE 2011: 3796–3799.

  • [5]

    Barthel P, Schneider R, Bauer A, et al. Risk stratification after acute myocardial infarction by heart rate turbulence. Circulation 2003; 108: 1221–1226. [PubMed] [Crossref]

  • [6]

    Bauer A, Schmidt G. Heart rate turbulence. J Electrocardiol 2003; 36: 89–93. [Crossref] [PubMed]

  • [7]

    Bauer A, Malik M, Schmidt G, et al. Heart rate turbulence: standards of measurement, physiological interpretation, and clinical use: International Society for Holter and Noninvasive Electrophysiology Consensus. J Am Coll Cardiol 2008; 52: 1352–1366. [Web of Science]

  • [8]

    Berkowitsch A, Zareba W, Neumann T, et al. Risk stratification using heart rate turbulence and ventricular arrhythmia in MADIT II: usefulness and limitations of a 10-minute Holter recording. Ann Noninvasive Electrocardiol 2004; 9: 270–279. [PubMed] [Crossref]

  • [9]

    Chang C-C, Lin C-J. LIBSVM: a library for support vector machines. ACM Trans Intelligent Systems Technol 2011; 2: 27:1–27:27. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm/.

  • [10]

    Clarke JM, Shelton JR, Venning GR, Hamer J, Taylor S. The rhythm of the normal human heart. Lancet 1976; 308: 508–512.

  • [11]

    de Chazal P, Reilly RB. A patient-adapting heartbeat classifier using ECG morphology and heartbeat interval features. IEEE Trans Biomed Eng 2006; 53: 2535–2543. [Crossref]

  • [12]

    de Chazal P, O’Dwyer M, Reilly RB. Automatic classification of heartbeats using ECG morphology and heartbeat interval features. IEEE Trans Biomed Eng 2004; 51: 1196–1206.

  • [13]

    Francis J, Watanabe MA, Schmidt G. Heart rate turbulence: a new predictor for risk of sudden cardiac death. Ann Noninvasive Electrocardiol 2005; 10: 102–109. [PubMed] [Crossref]

  • [14]

    Ghaffari A, Homaeinezhad MR, Daevaeiha MM. High resolution ambulatory Holter ECG events detection-delineation via modified multi-lead wavelet-based features analysis: detection and quantification of heart rate turbulence. Exp Syst Appl 2011; 38: 5299–5310. [Crossref] [Web of Science]

  • [15]

    Goldberger AL, Amaral LAN, Glass L, et al. Physio Bank, PhysioToolkit, and PhysioNet: components of a new reserach resource for complex physiologic signals. Circulation 2000; 101: e215–e220. [Crossref]

  • [16]

    Haissaguerre M, Jas P, Shah DC, et al. Spontaneous initiation of atrial fibrillation by ectopic beats originating in the pulmonary veins. N Engl J Med 1998; 339: 659–666.

  • [17]

    Huikuri HV, Seppänen T, Koistinen MJ, et al. Abnormalities in beat-to-beat dynamics of heart rate before the spontaneous onset of life-threatening ventricular tachyarrhythmias in patients with prior myocardial infarction. Circulation 1996; 93: 1836–1844. [Crossref] [PubMed]

  • [18]

    Keller DUJ, Weiss DL, Dössel O, Seemann G. Influence of IKS heterogeneities on the genesis of the T-wave: a computational evaluation. IEEE Trans Biomed Eng 2012; 59: 311. [Crossref] [Web of Science]

  • [19]

    Kotler MN, Tabazanki B, Mower MM, Tominaga S. Prognostic significance of ventricular ectopic beats with respect to sudden death in the late postinfarction period. Circulation 1973; 47: 959–966. [Crossref] [PubMed]

  • [20]

    Lepeschkin E, Surawicz B. The measurement of the qt interval of the electrocardiogram. Circulation 1952; 6: 378–388. [Crossref]

  • [21]

    Lown B, Wolf M. Approaches to sudden death from coronary heart disease. Circulation 1971; 44: 130–142. [PubMed] [Crossref]

  • [22]

    Schmidt G, Malik M, Barthel P, et al. Heart-rate turbulence after ventricular premature beats as a predictor of mortality after acute myocardial infarction. Lancet 1999; 353: 1390–1396.

  • [23]

    Schneider R, Röck A, Barthel P, Malik M, Camm AJ, Schmidt G. Heart rate turbulence: rate of frequency decrease predicts mortality in chronic heart disease patients. PACE 1999; 22: 879.

  • [24]

    Stoica P, Moses RL. Introduction to spectral analysis, vol. 89. Upper Saddle River, NJ: Prentice-Hall 1997.

  • [25]

    Watanabe MA. Heart rate turbulence: a review. Indian Pacing Electrophysiol J 2003; 3: 10. [PubMed]

  • [26]

    Zabel M, Acar B, Klingenheben T, Franz MR, Hohnloser SH, Malik M. Analysis of 12-lead T-wave morphology for risk stratification after myocardial infarction. Circulation 2000; 102: 1252–1257.

About the article

Corresponding author: Gustavo Lenis, Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Kaiserstrasse 12, 76131 Karlsruhe, Germany, Phone: +49-179-9499346, Fax: +49-721-60842789


Received: 2012-12-11

Accepted: 2013-01-09

Published Online: 2013-02-14

Published in Print: 2013-04-01


Citation Information: Biomedizinische Technik/Biomedical Engineering, ISSN (Online) 1862-278X, ISSN (Print) 0013-5585, DOI: https://doi.org/10.1515/bmt-2012-0114. Export Citation

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

[1]
Gustavo Lenis, Nicolas Pilia, Tobias Oesterlein, Armin Luik, Claus Schmitt, and Olaf Dössel
Biomedical Engineering / Biomedizinische Technik, 2015, Volume 0, Number 0
[2]
Tobias Georg Oesterlein, Gustavo Lenis, Dan-Timon Rudolph, Armin Luik, Bhawna Verma, Claus Schmitt, and Olaf Dössel
Journal of Electrocardiology, 2015, Volume 48, Number 2, Page 171

Comments (0)

Please log in or register to comment.
Log in