Detection of ventricular fibrillation by sequential testing

Yi Sheng Zhu, Nitish V. Thakor

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


Ventricular fibrillation (VF) must be accurately detected by an automatic implantable cardioconverter-defibrillator and must also be discriminated from ventricular tachycardia (VT) and supraventricular tachycardia (SVT). A sequential decision rule is described to discriminate probability distributions of VF from VT and SVT. Intracardiac signals are first converted to binary sequences by comparison with a threshold. Probability distributions of threshold-crossing intervals are determined. The sequential test calculates a log-likelihood function and compares that with preset detection thresholds. The thresholds are set so as to result in desired test accuracy. Essentially, the sequential algorithm trades off the time to reach decision (number of sequential decision steps) with accuracy. In a study of 170 electrograms from humans, 95.3% of VF signals are classified in 3 s, 97.6% in 5 s, and 100% in 7 s. The sequential algorithm offers ease of implementation for implantable devices and excellent performance.

Original languageEnglish (US)
Pages (from-to)325-328
Number of pages4
JournalComputers in cardiology
StatePublished - Sep 1 1988
EventComputers in Cardiology 1988 - Washington, DC, USA
Duration: Sep 25 1988Sep 28 1988

ASJC Scopus subject areas

  • Computer Science Applications
  • Cardiology and Cardiovascular Medicine


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