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We hypothesize that the analysis of the ventricular electrogram onset (EGM onset) can discriminate between SVT and VT to obtain a simultaneous increase in sensitivity and specificity. We discuss our analysis of EGMs obtained during SVT and VT together with their preceding SRs in 38 SVT and 68 VT far field records from 16 patients. The, algorithmic implementation and the preprocessing tasks were performed through the support vector method (SVM), avoiding the overfitting by means of the statistical bootstrap resampling. To improve the safety for an individual patient, two new methods of incremental learning, based on the SVM, are proposed and tested on an independent set of spontaneous arrhythmia episodes.