Probability density function revisited: improved discrimination of VF using a cycle length corrected PDF

The probability density function (PDF) describes the fraction of time an electrogram signal spends at the baseline. In normal rhythm the signal is at baseline during the period between electrogram complexes, while in fibrillation the signal exhibits continuous activity and spends little time at baseline. However, time spent at the baseline is dependent on the rate of the rhythm, which limits the ability of the PDF algorithm to discriminate ventricular fibrillation from fast nonfibrillatory rhythms. A cycle length corrected version of the PDF algorithm has been formulated, which only examines the electrical activity between detected beats. The algorithm was developed utilizing a training set of 77 endocardial recordings and tested utilizing a test set of 90 endocardial and 56 epicardial recordings. Ventricular fibrillation was detected with 100% sensitivity and 98% specificity.