Early signs of critical slowing down in heart surface electrograms of ventricular fibrillation victims

Berend Nannes, Rick Quax, Hiroshi Ashikaga, Mélèze Hocini, Remi Dubois, Olivier Bernus, Michel Haïssaguerre

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Ventricular fibrillation (VF) is a dangerous type of cardiac arrhythmia which, without intervention, almost always results in sudden death. Implantable automatic defibrillators are among the most successful devices to prevent sudden death by automatically applying a shock to the heart when fibrillation occurs. However, the electric shock is very painful and could lead to dangerous situations when a patient is, for example, driving or biking. An early warning signal for VF could reduce the risk in such situations or, in the future, reduce the need for defibrillation altogether. Here, we test for the presence of critical slowing down (CSD), which has proven to be an early warning indicator for critical transitions in a range of different systems. CSD is characterized by a buildup of autocorrelation; we therefore study the residuals of heart surface electrocardiograms (ECGs) of patients that suffered VF to investigate if we can measure positive trends in autocorrelation. We consider several methods to extract these residuals from the original signals. For three out of four VF victims, we find a significant amount of positive autocorrelation trends in the residuals, which might be explained by CSD. We show that these positive trends may not be measurable from the original body surface ECGs, but only from certain areas around the heart surface. We argue that additional experimental studies involving heart surface ECG data of subjects that did not suffer VF are required to quantify the prediction accuracy of the promising results we get from the data of VF victims.

Original languageEnglish (US)
Title of host publicationComputational Science – ICCS 2020 - 20th International Conference, Proceedings
EditorsValeria V. Krzhizhanovskaya, Gábor Závodszky, Michael H. Lees, Peter M.A. Sloot, Peter M.A. Sloot, Peter M.A. Sloot, Jack J. Dongarra, Sérgio Brissos, João Teixeira
PublisherSpringer Science and Business Media Deutschland GmbH
Pages334-347
Number of pages14
ISBN (Print)9783030504229
DOIs
StatePublished - 2020
Event20th International Conference on Computational Science, ICCS 2020 - Amsterdam, Netherlands
Duration: Jun 3 2020Jun 5 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12140 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Computational Science, ICCS 2020
Country/TerritoryNetherlands
CityAmsterdam
Period6/3/206/5/20

Keywords

  • Critical slowing down
  • Critical transition
  • Early warning signal
  • Ventricular fibrillation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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