Revolutionizing Cardiac Care: Deep Learning for Arrhythmia Detection

Abstract

Cardiac arrhythmia is a condition where heartbeat is irregular. The goal of this paper is to apply deep 
learning techniques in the diagnosis of cardiac arrhythmia using ECG signals with minimal possible 
data pre-processing. This paper employed one dimensional convolutional neural network (1D-CNN), 
recurrent structures such as long short-term memory (LSTM) to automatically detect the abnormality. 
Unlike the conventional analysis methods, the proposed method utilizes the principal component 
analysis (PCA) for feature extraction.