Signal Analysis For Cardiac Electrical Activation Studies
The aim of this study is to determine if some of the characteristics of reconstructed unipolar electrograms from the noncontact mapping system can be used to detect epicardial and to differentiate it from endocardial electrical activation in a canine heart. This would help the electrophysiologist know where exactly the origin of ventricular tachycardia or the critical point in tissue is located. Following this, arrhythmia can be successfully treated by ablating that part of the tissue of the heart. Virtual electrograms were recorded while pacing the right ventricle of an open-chest dog at multiple endocardial and epicardial sites using the commercially available noncontact mapping system (EnSite Array™ Catheter 3000). The endocardial and epicardial paced virtual electrograms from the juxtaposing sites allow for analyzing systematically the differences in their morphologies. Maximal dV / dt, area under the depolarization curve and latency extracted from unipolar electrograms demonstrated significant difference between epicardial and endocardial pacing sites with a p-value of less than 0.01 in all three cases. The above features were fed to a linear discriminant analysis based classifier and high classification accuracy was achieved. Therefore, reliable criteria can be proposed to allow for discrimination of an endocardial versus epicardial origin of electrical activation. And also the endocardial and epicardial paced virtual electrograms from the juxtaposing sites allows for an estimate of the transfer function of the myocardium in different positions of the right ventricles of a canine heart. The transfer function estimation will aid in better mathematical modeling of myocardium and could be a sensitive measure of myocardial homogeneity and arrhythmic foci localization.Another study was done on a human heart. This study was to evaluate the ability of virtual electrograms to predict abnormal bipolar electrograms. We tested the hypothesis of maxdV/dt, filtering and optimized DSM threshold. This allows better identification of abnormal myocardial substrate traditionally defined by contact bipolar mapping in human RVOT.