Atrial Fibrillation Detection and ECG Classification based on CNN-BiLSTM

11/12/2020
by   Jiacheng Wang, et al.
0

It is challenging to visually detect heart disease from the electrocardiographic (ECG) signals. Implementing an automated ECG signal detection system can help diagnosis arrhythmia in order to improve the accuracy of diagnosis. In this paper, we proposed, implemented, and compared an automated system using two different frameworks of the combination of convolutional neural network (CNN) and long-short term memory (LSTM) for classifying normal sinus signals, atrial fibrillation, and other noisy signals. The dataset we used is from the MIT-BIT Arrhythmia Physionet. Our approach demonstrated that the cascade of two deep learning network has higher performance than the concatenation of them, achieving a weighted f1 score of 0.82. The experimental results have successfully validated that the cascade of CNN and LSTM can achieve satisfactory performance on discriminating ECG signals.

READ FULL TEXT

page 1

page 2

page 3

page 4

08/27/2019

Complex Deep Learning Models for Denoising of Human Heart ECG signals

Effective and powerful methods for denoising real electrocardiogram (ECG...
05/18/2020

DENS-ECG: A Deep Learning Approach for ECG Signal Delineation

Objectives: With the technological advancements in the field of tele-hea...
05/14/2020

Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation

The electrocardiogram (ECG) is one of the most extensively employed sign...
08/18/2021

ECG-Based Heart Arrhythmia Diagnosis Through Attentional Convolutional Neural Networks

Electrocardiography (ECG) signal is a highly applied measurement for ind...
08/27/2020

Teaching a Machine to Diagnose a Heart Disease; Beginning from digitizing scanned ECGs to detecting the Brugada Syndrome (BrS)

Medical diagnoses can shape and change the life of a person drastically....
05/05/2022

Development of Interpretable Machine Learning Models to Detect Arrhythmia based on ECG Data

The analysis of electrocardiogram (ECG) signals can be time consuming as...
08/31/2021

Multistage Pruning of CNN Based ECG Classifiers for Edge Devices

Using smart wearable devices to monitor patients electrocardiogram (ECG)...