Analysis and visualization of intracardiac electrograms in diagnosis and research: Concept and application of KaPAVIE.

Background And Objective: Progress in biomedical engineering has improved the hardware available for diagnosis and treatment of cardiac arrhythmias. But although huge amounts of intracardiac electrograms (EGMs) can be acquired during electrophysiological examinations, there is still a lack of software aiding diagnosis. The development of novel algorithms for the automated analysis of EGMs has proven difficult, due to the highly interdisciplinary nature of this task and hampered data access in clinical systems.

Removing ventricular far-field signals in intracardiac electrograms during stable atrial tachycardia using the periodic component analysis.

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.