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). METHODS: Twenty-four-hour ambulatory atrial electrograms were recorded from continuous telemetry of digital pacemakers. Half of the recording was used for collecting two individual morphology parameters that discriminated P-waves from FFRWs in every patient (learning phase). The other half was used to test the MORPH algorithm against traditional methods (classification phase). RESULTS: In 44/48 patients, data were suitable for analysis. Average P and FFRW amplitudes were 1.96 mV versus 0.61 mV (P < 0.001). The interval between ventricular events and FFRW oversensing (VA interval) averaged at 14 ms during sensing and at 118 ms during pacing in the ventricle. Compared to nominal ("Factory") settings, the MORPH algorithm improved the sensitivity for P-wave recognition from 97.2% to 99.2%, the specificity from 91.9% to 99.96%, and the accuracy from 95.3% to 99.4% (P < 0.01 for all). CONCLUSIONS: By improving atrial signal discrimination, morphology analysis of atrial electrograms allows for high atrial sensitivity settings, and potentially improves the reliability of atrial arrhythmia diagnostics in heart rhythm devices.

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. Digital processing of the atrial intracardiac electrogram (IEGM) signals (8 bit, 800 samples/s) included filtering and calculation of the maximum amplitude and slope of the detected events. The form parameter was calculated, being the sum of the most negative value of the amplitude and that of the slope of the detected event. The algorithm collects form parameter data of P waves and FFRWs and composes histograms of these data. A sufficiently large gap between the FFRW and P wave histograms allows discrimination of these two signals based on form parameters. Three independent observers reviewed the reliability of classification with this algorithm. Sensitivity and specificity of FFRW detection were 99.63% and 100%, respectively, and no P waves were falsely classified. It can be concluded that this novel DSP algorithm shows excellent discrimination of FFRWs under off-line conditions and justify the implementation of this algorithm in future pacemakers for real-time discrimination between P waves and FFRWs. This method prevents false mode switching and allows correct and immediate intervention pacing for atrial tachyarrhythmias.