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Related Experiment Video

Updated: Jul 17, 2026

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Published on: July 20, 2022

QRST cancellation using bayesian estimation for the auricular fibrillation analysis.

O Meste¹, N Serfaty

¹University of Nice-Sophia Antipolis, Lab. I3S, Sophia Antipolis, France.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

|February 7, 2007

Summary

This study introduces a novel Bayesian approach for accurately estimating atrial fibrillation (AF) signals from ECGs. The method provides precise global and local AF signal estimation without spurious R-wave oscillations.

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Behavioral Determination of Stimulus Pair Discrimination of Auditory Acoustic and Electrical Stimuli Using a Classical Conditioning and Heart-rate Approach

Behavioral Determination of Stimulus Pair Discrimination of Auditory Acoustic and Electrical Stimuli Using a Classical Conditioning and Heart-rate Approach

Published on: June 6, 2012

Area of Science:

Biomedical Engineering
Signal Processing
Cardiology

Background:

Accurate extraction of atrial fibrillation (AF) signals from electrocardiograms (ECGs) is crucial for frequency analysis and atrioventricular node modeling.
Precision in AF amplitude estimation is vital for reliable cardiac modeling.

Purpose of the Study:

To propose and evaluate a novel Bayesian approach for AF signal estimation.
To assess the performance of the proposed method against classical and modern techniques.

Main Methods:

Development of an AF estimator utilizing a Bayesian framework.
Comparison with Average Beat Subtraction (ABS) and Blind Source Separation (BSS) techniques.
Validation on a small dataset of ECG examples.

Main Results:

The proposed Bayesian method demonstrates accurate global estimation of the AF signal.
Local estimation is precise, avoiding spurious oscillations near the R wave.
The a priori knowledge required for effective estimation is minimal.

Conclusions:

The Bayesian approach offers superior accuracy for AF signal extraction compared to ABS and BSS.
The method provides reliable local and global AF amplitude estimations, essential for cardiac modeling.
This technique advances the accuracy of AF signal analysis in ECGs.