Towards End-to-End ECG Classification With Raw Signal Extraction and Deep Neural Networks

IEEE Journal of Biomedical and Health Informatics
Sean Shensheng XuChi-Chung Cheung

Abstract

This paper proposes deep learning methods with signal alignment that facilitate the end-to-end classification of raw electrocardiogram (ECG) signals into heartbeat types, i.e., normal beat or different types of arrhythmias. Time-domain sample points are extracted from raw ECG signals, and consecutive vectors are extracted from a sliding time-window covering these sample points. Each of these vectors comprises the consecutive sample points of a complete heartbeat cycle, which includes not only the QRS complex but also the P and T waves. Unlike existing heartbeat classification methods in which medical doctors extract handcrafted features from raw ECG signals, the proposed end-to-end method leverages a deep neural network for both feature extraction and classification based on aligned heartbeats. This strategy not only obviates the need to handcraft the features but also produces optimized ECG representation for heartbeat classification. Evaluations on the MIT-BIH arrhythmia database show that at the same specificity, the proposed patient-independent classifier can detect supraventricular- and ventricular-ectopic beats at a sensitivity that is at least 10% higher than current state-of-the-art methods. More importantly, there is a...Continue Reading

Citations

May 22, 2019·Netherlands Heart Journal : Monthly Journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation·J W BenjaminsP van der Harst
Feb 15, 2020·Sensors·Beanbonyka RimMin Hong
Dec 22, 2020·Computers in Biology and Medicine·Yao GuoWei Chen
Oct 30, 2020·Frontiers in Physiology·Yongbo LiangZhencheng Chen
Jul 14, 2020·Computers in Biology and Medicine·Shenda HongJimeng Sun
Apr 4, 2021·Bioengineering·Andrea BizzegoGianluca Esposito
May 18, 2021·International Journal of Cardiology·Jin-Yu SunXiang-Qing Kong
May 20, 2021·Computational and Mathematical Methods in Medicine·Enbiao JingIvan Ganchev
Jul 25, 2021·Scientific Reports·Sahil Dalal, Virendra P Vishwakarma

❮ Previous
Next ❯

Related Concepts

Related Feeds

Arrhythmia

Arrhythmias are abnormalities in heart rhythms, which can be either too fast or too slow. They can result from abnormalities of the initiation of an impulse or impulse conduction or a combination of both. Here is the latest research on arrhythmias.

Atrial Fibrillation

Atrial fibrillation is a common arrhythmia that is associated with substantial morbidity and mortality, particularly due to stroke and thromboembolism. Here is the latest research.

© 2022 Meta ULC. All rights reserved