Classification of Cardiac Arrhythmia Using Fractal Dimension and Convolutional Neuronal Networks CNN

Abstract

Cardiovascular disease is currently one of the leading dangerous diseases that endanger human health and the number of people suffering from it is increasing. Healthcare professionals rely heavily on electrocardiograms (ECGs) to diagnose cardiovascular disease because they accurately depict the condition of the heart. The connection between the lack of medical resources and the increase in the number of patients becomes even clearer in this situation. The use of computer-aided cardiovascular disease diagnosis has become important, making the study of automatic ECG classification methods extremely important in practice. In this study, we present a method combining fractal dimension and CNN convolutional neural network to classify cardiovascular diseases.