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Automatic and efficient R wave discrimination in the right atrium using a two-state hidden Markov model.

W Sun1, W Combs, E Panken

  • 1Guidant Corp., Minneapolis, Minnesota, USA.

Journal of Cardiovascular Electrophysiology
|April 21, 1999
PubMed
Summary

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A new hidden Markov model accurately detects far-field R waves in atrial electrograms, improving pacemaker function and arrhythmia detection for patients with implantable pacing systems.

Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Signal Processing

Background:

  • Distinguishing far-field R waves from atrial events in electrograms (EGMs) is a challenge for current pacemakers.
  • Existing methods like adjusting refractory periods offer suboptimal performance.
  • Reliable detection of far-field R waves can prevent atrial undersensing/oversensing and enhance arrhythmia detection.

Purpose of the Study:

  • To develop and validate a novel method for accurate far-field R wave detection in atrial EGMs.
  • To improve atrial arrhythmia management in patients with implantable pacing systems.

Main Methods:

  • Collected unipolar atrial and ventricular electrograms (EGMs) from 25 patients undergoing pacemaker procedures.
  • Developed a two-state hidden Markov model (HMM) for discriminating far-field R waves and P waves.

Related Experiment Videos

  • Evaluated the HMM's sensitivity and positive predictivity using visually marked EGMs as the control.

    • Main Results:

    • The HMM achieved 94% sensitivity and 98.3% positive predictivity for far-field R wave detection.
    • Far-field R wave rejection demonstrated high performance with 98.8% sensitivity and 99.1% positive predictivity.
    • The model proved reliable and accurate in analyzing patient EGMs.

    Conclusions:

    • The two-state HMM provides a reliable and accurate method for far-field R wave detection in the right atrium.
    • This technology has the potential to significantly enhance atrial arrhythmia management for pacemaker patients.