DETECTION OF ACTIVATION IN ELECTROGRAMS USING NEURAL-NETWORK-TRAINED PREPROCESSING OF INTRACARDIAC ELECTROGRAMS

• Main Authors: KATZ, Natan Sharon, KUZHNAREVA, Elena Igorevna, KIRYASOV, Andrey Evgenyevich, SHOVKUN, Aleksey Vladimirovich, RAVUNA, Eliyahu
• Format: Patent
• Language: English; French; German
• Published: 16.02.2022
• Subjects: DIAGNOSIS; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; HUMAN NECESSITIES; HYGIENE; IDENTIFICATION; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; MEDICAL OR VETERINARY SCIENCE; PHYSICS; SURGERY

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.