New methods for estimating local electrical activation rate during atrial fibrillation

Area of Science:

• Cardiology
• Biomedical Engineering
• Signal Processing

Background:

• Dominant frequency (DF) analysis has limitations in characterizing atrial fibrillation (AF).
• Improved methodologies are needed for accurate AF signal analysis.
• This study addresses the need for non-frequency-domain analysis of AF signals.

Purpose of the Study:

• To develop novel methods for analyzing AF signals without frequency transformation.
• To compare these new methods against traditional DF analysis.
• To validate the developed methods using both real patient data and simulated signals.

Main Methods:

• Electrograms from 11 AF patients were analyzed.
• Two new methods were employed: time complexes (TC) and ensemble average (EA) analysis.
• Methods were compared using AF patient data and simulations with controlled noise, amplitude, and phase variations.

Main Results:

• Mean atrial rates were similar across methods (EA: 5.71 Hz, TC: 5.96 Hz, DF: 5.72 Hz).
• The ensemble average (EA) method demonstrated superior robustness against additive random noise and amplitude variations compared to DF and TC.
• All methods accurately estimated rates in atrial flutter, validating their performance under static conditions.

Conclusions:

• Accurate atrial rate estimation is dependent on signal periodicity and susceptible to random noise.
• The ensemble average (EA) method provides reliable atrial rate estimation, particularly in the presence of significant noise.
• The EA method offers a valuable alternative for AF signal analysis, outperforming traditional DF analysis in noisy conditions.