AUTOCORRELATION ANALYSIS OF VENTRICULAR FIBRILLATION SIGNALS.

Accurate recognition of a ventricular fibrillation (VF) signal, especially to separate it from ventricular tachycardia (VT), is important for the operation of automatic defibrillators. The authors analyze intracardiac electrogram signals by means of an autocorrelation function (ACF) that operates on short-term data. They observe that in the case of normal sinus rhythm and VT, the characteristic peaks in the ACF can be fit by a linear regression curve (reflecting periodicity and uniform amplitude). This is not the case for VF, and therefore serves as a reliable test. In 31 episodes, repeated tests of 3 successive segments, this VF detection strategy resulted in 100% sensitivity and specificity.