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.
ASJC Scopus subject areas
- Computer Science Applications
- Cardiology and Cardiovascular Medicine