Related Experiment Video
Updated: Sep 20, 2025

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Published on: January 8, 2013
Atrioventricular Synchrony Algorithm Modeling of a Leadless Pacemaker Family: A Virtual Patient Analysis
Miguel A Leal1, Todd Sheldon2, Keelia Escalante2
1Emory University School of Medicine, Atlanta, GA, USA. miguel.a.leal@emory.edu.
Purpose:
To assess the impact of enhancements to the Atrioventricular Synchrony (AVS) algorithms of a next generation Micra leadless pacemaker (Micra AV2).
Methods:
Accelerometer data were extracted from the AccelAV clinical study and were used to create virtual patients. A series of Monte Carlo simulations were run for each virtual patient to compare an enhanced Atrial Sensing Setup algorithm and Auto + A3 Threshold algorithm vs. original algorithms. A real-world survey was also conducted to observe clinical time savings from AVS programming burden reduction.
Results:
The enhanced Atrial Sensing Setup in Micra AV2 devices demonstrated > 70% AVS in 27 of 30 (90%) patients while 13 of 30 (43%) Micra AV patients had > 70% AVS (p < 0.001) with no manual programming. The Micra AV2 Auto + A3 Threshold without additional manual programming demonstrated improved overall ambulatory AVS in the 80-100 bpm range (84.1%). Based upon survey results, the enhanced Atrial Sensing Setup algorithm accounted for an estimated reduction in median device check time of 13 min per patient.
Conclusions:
Simulation-based analyses of the Micra AV2 leadless pacemaker projected significant improvements in automatic AVS at high sinus rates and an increase in the number of patients with > 70% AVS without clinician programming. Real-world survey results reported a reduction in device check time with the improvements.
Significance:
Improvements in the AVS algorithms in Micra AV2 allow for better automatic AVS at higher heart rates and reduced clinic utilization burden.
Related Concept Videos
Mechanism of Cardiac Arrhythmias
ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias
Electrophysiology of Normal Cardiac Rhythm
Dysrhythmias I: Introduction
Electrocardiogram Fundamentals
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
Dysrhythmias V: Evaluating Dysrhythmias

