ABSTRACT
BACKGROUND: Intracardiac electrograms are an indispensable part during diagnosis of supraventricular arrhythmias, but atrial activity (AA) can be obscured by ventricular far-fields (VFF). Concepts based on statistical independence like principal component analysis (PCA) cannot be applied for VFF removal during atrial tachycardia with stable conduction. METHODS: A database of realistic electrograms containing AA and VFF was generated. Both PCA and the new technique periodic component analysis (πCA) were implemented, benchmarked, and applied to clinical data. RESULTS: The concept of πCA was successfully verified to retain compromised AA morphology, showing high correlation (cc=0.98±0.01) for stable atrial cycle length (ACL). Performance of PCA failed during temporal coupling (cc=0.03±0.08) but improved for increasing conduction variability (cc=0.77±0.14). Stability of ACL was identified as a critical parameter for πCA application. Analysis of clinical data confirmed these findings. CONCLUSION: πCA is introduced as a powerful new technique for artifact removal in periodic signals. Its concept and performance were benchmarked against PCA using simulated data and demonstrated on measured electrograms.
