Separation of Ventricular Tachycardia From Sinus Rhythm Using a Practical, Real‐Time Template Matching Computer System

Template matching morphology analysis of the infra‐ventricular electrogram (IVEG) has been proposed for inclusion in implantable cardioverter defibrillators (ICDs) to reduce the number of false ventricular tachyarrhythmia detections caused by rate overlap between ventricular tachycardia (VT) and sinus tachycardia and for supraventricular tachycardia. Template matching techniques have been developed that reduce the computational complexity while preserving the perceived important aspects of electrogram amplitude and baseline independence found in such computationally unsolved methods as correlation waveform analysis (CWA). These methods have been shown to work as well as CWA for separation of VT, however, they have not been proven in real‐time on a system that incorporates many of the constraints of present day ICDs. The present study was undertaken with two purposes: (1) to determine if real‐time IVEG template matching analysis on an ICD sensing emulator was accurate in separating VT from sinus rhythm (SR) electrograms; and (2) to compare amplitude normalized area of difference (NAD) with signature analysis (SIG), a new, computationally less expensive technique that normalizes for amplitude variation within the expected physiological level of variability. In this study, JVEGs, obtained from 16 patients who underwent electrophysiological study (EPS) for evaluation of sustained ventricular arrhythmia, were digitized to 250 Hz with 6‐bit quantization after filtering (16‐44 Hz) and differentiation. After an SR template was selected and periodically updated, it was compared to subsequent IVEGs using NAD and SIG. In general, SIG calculates the fraction of samples occurring outside template window boundaries. Eleven‐beat running medians from beat‐by‐beat NAD and SIG results were determined. The maximum median during VT was subtracted from the minimum median during SR with the result equal to the separation margin. With the minimum separation threshold set to 0 (i.e., no overlap), 0.1, and 0.2, NAD separated 16/16, 14/16, and 9/16 VTs, while SIG separated 15/16, 14/16, and 13/16 VTs, respectively. While NAD separated more VT episodes on the strict basis of no overlap, SIG separated more than NAD as the safety margin was further increased. Conclusions: (1) template matching morphology techniques can potentially be implemented in ICDs; (2) using a patient specific threshold, NAD and SIG appear capable of separating VTfrom SR in most patients; and (3) SIG and NAD appear to be similar in accuracy. Thus, SIG may be preferable since it significantly reduces the computational load.