Morphology-enhanced atrial event classification improves sensing in pacemakers.

Background: In atrial-based pacing, appropriate therapy and reliable diagnostics depend on detection and discrimination of atrial signals. Accurate classification of atrial events is mainly confounded by oversensing of ventricular far-field R-wave signals (FFRW), but attempts to reject FFRWs by manipulating atrial sensitivity and/or postventricular atrial blanking period (PVAB) may result in undersensing (especially of atrial fibrillation, AF) or in 2:1 atrial flutter detection. The objective of this study is therefore to evaluate if such methods can be improved by morphology-enhanced atrial event classification (MORPH).

Form analysis using digital signal processing reliably discriminates far-field R waves from P waves.

The correct detection of atrial arrhythmias by pacemakers is often limited by the presence of far-field R waves (FFRWs) in the atrial electrogram. Digital signal processing (DSP) of intracardiac signals is assumed to provide improved discrimination between P waves and FFRWs when compared to current methods. For this purpose, 100 bipolar and unipolar intracardiac atrial recordings from 31 patients were collected during pacemaker replacement and used for the off-line application of a novel DSP algorithm.