Detecting ventricular tachycardia and fibrillation by complexity measure

Xu Sheng Zhang, Yi Sheng Zhu, Nitish V. Thakor, Zhi Zhong Wang

Research output: Contribution to journalArticle

Abstract

Sinus rhythm (SR), ventricular tachycardia (VT) and ventricular fibrillation (VF) belong to different nonlinear physiological processes with different complexity. In this study, we present a novel, and computationally fast method to detect VT and VF, which utilizes a complexity measure suggested by Lempel and Ziv [1]. For a specific window length (i.e., the length of data segment to be analyzed), the method first generates a 0-1 string by comparing the raw electrocardiogram (ECG) data to a selected suitable threshold. The complexity measure can be obtained from the 0-1 string only using two simple operations, comparison and accumulation. When the window length is 7 s, the detection accuracy for each of SR, VT, and VF is 100% for a test set of 204 body surface records (34 SR, 85 monomorphic VT, and 85 VF). Compared with other conventional time- and frequency-domain methods, such as rate and irregularity, VF-filter leakage, and sequential hypothesis testing, the new algorithm is simple, computationally efficient, and well suited for real-time implementation in automatic external defibrillators (AED's).

Original languageEnglish (US)
Pages (from-to)548-555
Number of pages8
JournalIEEE Transactions on Biomedical Engineering
Volume46
Issue number5
DOIs
StatePublished - May 12 1999

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Keywords

  • Arrhythmia detection
  • Automatic external defibrillators
  • Complexity measure
  • Ventricular fibrillation

ASJC Scopus subject areas

  • Biomedical Engineering

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