Using the detail vector for neural network classification of electrocardiogram signals

Abstract

Using the detail vector for neural network classification of electrocardiogram signals

Kiladze M.R., Lyakhov P.A., Nagornov N.N.

Incoming article date: 01.10.2023

Diseases of the cardiovascular system are the main cause of death in the world. The main way to diagnose diseases of the cardiovascular system is to take an electrocardiogram of the patient. Automatic processing of electrocardiogram signals will allow doctors to quickly identify heart problems in a patient. This article presents a method for calculating the detail vector for neural network processing of a twelve-channel electrocardiogram signal. Adding a detail vector to the electrocardiogram signals improves the classification accuracy to 87.50%. The proposed method can be used to automatically classify two or more channel electrocardiogram signals.

Keywords: electrocardiogram, recurrent neural network, neural network with long-term short memory, detailing vector, PhysioNet Computing in Cardiology Challenge 2021