Phase statistics approach to human ventricular fibrillation

Ming Chya Wu, Eiichi Watanabe, Zbigniew R. Struzik, Chin Kun Hu, Yoshiharu Yamamoto

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Ventricular fibrillation (VF) is known to be the most dangerous cardiac arrhythmia, frequently leading to sudden cardiac death (SCD). During VF, cardiac output drops to nil and, unless the fibrillation is promptly halted, death usually ensues within minutes. While delivering life saving electrical shocks is a method of preventing SCD, it has been recognized that some, though not many, VF episodes are self-terminating, and understanding the mechanism of spontaneous defibrillation might provide newer therapeutic options for treatment of this otherwise fatal arrhythmia. Using the phase statistics approach, recently developed to study financial and physiological time series, here, we reveal the timing characteristics of transient features of ventricular tachyarrhythmia (mostly VF) electrocardiogram (ECG) and find that there are three distinct types of probability density function (PDF) of phase distributions: uniform (UF), concave (CC), and convex (CV). Our data show that VF patients with UF or CC types of PDF have approximately the same probability of survival and nonsurvival, while VF patients with CV type PDF have zero probability of survival, implying that their VF episodes are never self-terminating. Our results suggest that detailed phase statistics of human ECG data may be a key to understanding the mechanism of spontaneous defibrillation of fatal VF.

Original languageEnglish
Article number051917
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume80
Issue number5
DOIs
Publication statusPublished - 20-11-2009

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

Fingerprint

Dive into the research topics of 'Phase statistics approach to human ventricular fibrillation'. Together they form a unique fingerprint.

Cite this