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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)

Abstract

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.

Keywords

Electrocardiographic alternans Adaptive match filter Electrocardiogram 

Notes

Conflict of Interest

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

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Università Politecnica delle MarcheAnconaItaly

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