P Wave and Far‐Field R Wave Detection in Pacemaker Patient Atrial Electrograms

Abstract

This study was undertaken to develop and test a morphology-based adaptive algorithm for real-time detection of P waves and far-field R waves (FFRWs) in pacemaker patient atrial electrograms. Cardiac event discrimination in right atrial electrograms has been a problem resulting in improper atrial sensing in implantable devices; potentially requiring clinical evaluation and device reprogramming. A morphology-based adaptive algorithm was first evaluated with electrograms recorded from 25 dual chamber pacemaker implant patients. A digital signal processing (DSP) system was designed to implement the algorithm and test real-time detection. In the second phase, the DSP implementation was evaluated in 13 patients. Atrial and ventricular electrograms were processed in real-time following algorithm training performed in the first few seconds for each patient. Electrograms were later manually annotated for comparative analysis. The sensitivity for FFRW detection in the atrial electrogram during off-line analysis was 92.5% (+/- 10.9) and the positive predictive value was 99.1% (+/- 1.8). Real-time P wave detection using a DSP system had a sensitivity of 98.9% (+/- 1.3) and a positive predictivity of 97.3% (+/- 3.5). FFRW detection had a sensitivity of 91.0% (+/- 12.4) and a positive predictivity of 97.1% (+/- 4.2) in atrial electrograms. DSP algorithm tested can accurately detect both P waves and FFRWs in right atrium real-time. Advanced signal processing techniques can be applied to arrhythmia detection and may eventually improve detection, reduce clinician interventions, and improve unipolar and bipolar lead sensing.

Management of Far‐Field R Wave Sensing for the Avoidance of Inappropriate Mode Switch in Dual Chamber Pacemakers: Results of the FFS‐Test Study

“…Usually, the atrial far‐field signal differs in shape and size from the atrial near‐field signal 15 . As morphology criteria for the detection of far‐field signals are not commercially available in current pacemakers, anti‐FFS programming focuses on the adjustment of the atrial sensitivity, on the retrospective rejection of atrial signals that constantly occur during a certain time frame before or after a ventricular event (PR logic algorithm in Medtronic AT 500 and EnRhythm pacemakers), or on the PVAB.…”

Atrial Near‐Field and Ventricular Far‐Field Analysis by Automated Signal Processing at Rest and During Exercise

“…13 However, a prerequisite for any real-time morphology analysis is a stable signal under different conditions. Our study shows for the first time by means of automated signal processing that the atrial signal …”

“…A single pacemaker device type was chosen to exclude the influence of different sense amplifiers and filters on the study result. Measurements were performed 7 ± 3 months (range [3][4][5][6][7][8][9][10][11][12][13][14] after implantation of the device and pacing leads. Patient age was 66 ± 10 years, 79% of patients were male.…”

Form Analysis Using Digital Signal Processing Reliably Discriminates Far‐Field R Waves from P Waves

“…Immediate detection of atrial tachyarrhythmias is, therefore, important to optimize device therapies for atrial arrhythmias like mode switching or antitachycardia pacing 3–9 . Accurate discrimination between FFRWs and premature atrial ectopic signals constitutes a specific problem since detection of atrial arrhythmias requires low sensing thresholds and minimal cross‐chamber blanking periods 10–12 . Currently, detection of premature atrial beats and tachyarrhythmias is accomplished via programmable algorithms based on atrial cycle length and atrial cycle regularity after analog signal filtering, since pacemakers are not able to continuously store long‐term intracardiac data as a reference for pattern recognition 7–10 .…”