Statistical validation of new template matching methods for detecting ventricular tachycardia

To improve over rate based algorithms for detection of pathological tachycardias by implantable antitachycardia devices, techniques based on morphological differences in ventricular electrograms during sinus rhythm or atrial fibrillation (SR/AF) and ventricular tachycardia (VT) have been proposed. Examined are the results of three proposed methods of intracardiac electrogram analysis for discriminating ventricular electrograms during VT from those during SR/AF: Correlation Waveform Analysis, the Bin Area Method, and the Derivative Area Method. It is demonstrated that the distribution of derived values from intracardiac analysis using these algorithms is not generally a normal (Gaussian) distribution. Nonparametric tolerance intervals are used to evaluate the performance of these algorithms in discriminating ventricular electrograms during VT from those during SR/AF