Electrocardiographic Alternans: A New Approach

  • Ilaria Marcantoni
  • Dalila Calabrese
  • Giorgia Chiriatti
  • Roberta Melchionda
  • Benedetta Pambianco
  • Giulia Rafaiani
  • Eleonora Scardecchia
  • Agnese Sbrollini
  • Micaela Morettini
  • Laura BurattiniEmail author
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 76)


Alternans is an electrophysiological phenomenon consisting in a beat-to-beat variation of the morphology of an electrocardiographic (ECG) waveform. Literature has particularly studied T-wave alternans (TWA) because it has been widely recognized as a noninvasive and clinically useful index to predict occurrence of malignant ventricular arrhythmias and, eventually, sudden cardiac death. Historically, alternans of other segments of ECG, like P wave (PWA), or QRS complex (QRSA) gained less interest than TWA, but this is an incomplete vision of the action potential (AP). AP is influenced by electrical activity of all myocardial cells, so it is reasonable that all ECG waveforms could be affected by alternans phenomenon. ECG alternans (ECGA) can be intended as the prevalent nature of alternans. This study aimed to use the heart-rate adaptive match filter (AMF) method, previously applied for TWA applications, to detect ECGA. AMF effectiveness was tested on simulated alternating ECG (alternans-amplitude range: 10 µV–200 µV), characterized by single- and multiple-wave alternans (always of the same amplitude and morphology). AMF method proved to be specific, being able to recognize ECGA absence, and particularly sensitive to TWA. In general, in case of singular-wave alternans, AMF correctly identified the type of alternans and correctly determined its amplitude (mean error: 0%). When TWA was combined to PWA or QRSA, only TWA was identified with an overestimation of its amplitude (mean error: 23%). In conclusion, overall AMF proved its effectiveness and specificity in revealing and discriminating ECGA.


Electrocardiographic alternans Adaptive match filter Electrocardiogram 


Conflict of Interest

All authors have no financial and personal relationships with other people or organizations that could inappropriately bias the work.


  1. 1.
    Burattini, L., Man, S., Fioretti, S., Di Nardo, F., Swenne, C.A.: Dependency of exercise-induced T-wave alternans predictive power for the occurrence of ventricular arrhythmias from heart rate. Ann. Noninvasive Electrocardiol. 20(4), 345–354 (2015)CrossRefGoogle Scholar
  2. 2.
    Adam, D.R., Smith, J.M., Akselrod, S., Nyberg, S., Powell, A.O., Cohen, R.J.: Fluctuations in T-wave morphology and susceptibility to ventricular fibrillation. J. Electrocardiol. 17(3), 209–218 (1984)CrossRefGoogle Scholar
  3. 3.
    Bigger, J.T., Bloomfield, D.M.: Microvolt T-wave alternans: an effective approach to risk stratification in ischemic cardiomyopathy?: Commentary. Nat. Clin. Pract. Cardiovasc. Med. 4(6), 300–301 (2007)CrossRefGoogle Scholar
  4. 4.
    Siniorakis, E., Arvanitakis, S., Tzevelekos, P., Giannakopoulos, N., Limberi, S.: P-wave alternans predicting imminent atrial flutter. Cardiol. J. 24(6), 706–707 (2017)CrossRefGoogle Scholar
  5. 5.
    Maury, P., Metzger, J.: Alternans in QRS amplitude during ventricular tachycardia. Pacing Clin. Electrophysiol. 25(2), 142–150 (2002)CrossRefGoogle Scholar
  6. 6.
    Burattini, L., Man, S., Swenne, C.A.: The power of exercise-induced T-wave alternans to predict ventricular arrhythmias in patients with implanted cardiac defibrillator. J. Healthc. Eng. 4(2), 167–184 (2013)CrossRefGoogle Scholar
  7. 7.
    Burattini, L., Bini, S., Burattini, R.: Repolarization alternans heterogeneity in healthy subjects and acute myocardial infarction patients. Med. Eng. Phys. 34(3), 305–312 (2012)CrossRefGoogle Scholar
  8. 8.
    Marcantoni, I., Cerquetti, V., Cotechini, V., Lattanzi, M., Sbrollini, A., Morettini, M., Burattini, L.: T-wave alternans in partial epileptic patients. In: 45th Computing in Cardiology Conference, Maastricht, pp. 1–4 (2018).
  9. 9.
    Man, S., De Winter, P.V., Maan, A.C., Thijssen, J., Borleffs, C.J.W., Van Meerwijk, W.P.M., Bootsma, M., Van Erven, L., Van Der Wall, E.E., Schalij, M.J., Burattini, L., Burattini, R., Swenne, C.A.: Predictive power of T-wave alternans and of ventricular gradient hysteresis for the occurrence of ventricular arrhythmias in primary prevention cardioverter-defibrillator patients. J. Electrocardiol. 44(4), 453–459 (2011)CrossRefGoogle Scholar
  10. 10.
    Armoundas, A.A., Tomaselli, G.F., Esperer, H.D.: Pathophysiological basis and clinical application of T-wave alternans. J. Am. Coll. Cardiol. 40(2), 207–217 (2002)CrossRefGoogle Scholar
  11. 11.
    Hopenfeld, B.: Mechanism for action potential alternans: the interplay between L-type calcium current and transient outward current. Heart Rhythm 3(3), 345–352 (2006)CrossRefGoogle Scholar
  12. 12.
    Brembilla-Perrot, B., Lucron, H., Schwalm, F., Haouzi, A.: Mechanism of QRS electrical alternans. Heart 77(2), 180–182 (1997)CrossRefGoogle Scholar
  13. 13.
    Burattini, L., Bini, S., Burattini, R.: Automatic microvolt T-wave alternans identification in relation to ECG interferences surviving preprocessing. Med. Eng. Phys. 33(1), 17–30 (2011)CrossRefGoogle Scholar
  14. 14.
    Burattini, L., Zareba, W., Burattini, R.: Adaptive match filter based method for time vs. amplitude characterization of microvolt ECG T-wave alternans. Ann. Biomed. Eng. 36(9), 1558–1564 (2008)CrossRefGoogle Scholar
  15. 15.
    Burattini, L., Zareba, W., Burattini, R.: Automatic detection of microvolt T-wave alternans in Holter recordings: effect of baseline wandering. Biomed. Signal Process. Control 1(2), 162–168 (2006)CrossRefGoogle Scholar
  16. 16.
    Burattini, L., Bini, S., Burattini, R.: Comparative analysis of methods for automatic detection and quantification of microvolt T-wave alternans. Med. Eng. Phys. 31(10), 1290–1298 (2009)CrossRefGoogle Scholar
  17. 17.
    Morettini, M., Marchesini, L., Pettinari, L.A., Tigrini, A., Marcantoni, I., Sbrollini, A., Burattini, L.: TWA simulator: a graphical user interface for t-wave alternans. In: 45th Computing in Cardiology Conference, Maastricht, pp. 1–4 (2018).
  18. 18.
    Bini, S., Burattini, L.: Quantitative characterization of repolarization alternans in terms of amplitude and location: what information from different methods? Biomed. Signal Process. Control 8(6), 675–681 (2013)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Università Politecnica delle MarcheAnconaItaly

Personalised recommendations