Detection of activation in electrograms using neural-network-trained preprocessing of intracardiac electrograms

• Main Authors: Andrey Evgenyevich Kiryasov, Eliyahu Ravuna, Natan Sharon Katz, Aleksey Vladimirovich Shovkun, Elena Igorevna Kuzhnareva
• Format: Patent
• Language: English; Hebrew
• Published: 01.03.2022

A method includes collecting a plurality of bipolar electrograms and respective unipolar electrograms of patients, the electrograms including annotations in which one or more human reviewers have identified and marked a window-of-interest and one or more activation times inside the window-of-interest. A ground truth data set is generated from the electrograms, for training at least one electrogram-preprocessing step of a Machine Learning (ML) algorithm. The ML algorithm is applied to the electrograms, to at least train the at least one electrogram-preprocessing step, so as to detect an occurrence of an activation in a given bipolar electrogram within the window-of-interest.