A two-dimensional clustering technique for identification of multiform ventricular complexes.

A computer algorithm for the identification of multiform ectopic ventricular complexes in 24-hour ambulatory electrocardiographic recordings is described. The clustering technique established regions, based on R-R interval and ST-segment slope, in a two-dimensional probability space based on the fit of each ventricular complex. The boundaries of any overlapping regions are analyzed using a Bayesian decision rule to minimize misclassification.