Swarm Decomposition Enhances the Discrimination of Cardiac Arrhythmias in Varied-Lead ECG Using ResNet-BiLSTM Network Activations

Mohanad Alkhodari, Georgios Apostolidis, Charilaos Zisou, Leontios J. Hadjileontiadis, Ahsan H. Khandoker

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

The standard screening tool for cardiac arrhythmias remains to be the 12-lead electrocardiography (ECG). Despite carrying rich information about different types of arrhythmias, it is considered bulky, high-cost, and often hard to use. In this study, we sought to investigate the efficiency of using 6-lead, 4-lead, 3 -lead, and 2-lead ECG in discriminating between 26 arrhythmia types and compare them with the standard 12-lead ECG. as part of PhysioNet/Computing in Cardiology 2021 Challenge. Our team, Care4MyHeart, developed a deep learning approach based on residual convolutional neural networks and Bi-directional long short term memory (ResNet-BiLSTM) to extract deep-activated features from ECG oscillatory components obtained using a novel swarm decomposition (SWD) algorithm. Alongside age and sex, these automated features were combined with hand-crafted features from heart rate variability and SWD components for training and classification. Our approach achieved a challenge score of 0.45, 0.43, 0.44, 0.43, and 0.42 using 10-fold cross-validation using the training set and 0.25, 0.23, 0.24, 0.22, and 0.20 using the hidden test set for 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead, respectively. Our team was ranked the 31/38 with an average all-lead test score of 0.22.

Original languageBritish English
Title of host publication2021 Computing in Cardiology, CinC 2021
PublisherIEEE Computer Society
ISBN (Electronic)9781665479165
DOIs
StatePublished - 2021
Event2021 Computing in Cardiology, CinC 2021 - Brno, Czech Republic
Duration: 13 Sep 202115 Sep 2021

Publication series

NameComputing in Cardiology
Volume2021-September
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Conference

Conference2021 Computing in Cardiology, CinC 2021
Country/TerritoryCzech Republic
CityBrno
Period13/09/2115/09/21

Fingerprint

Dive into the research topics of 'Swarm Decomposition Enhances the Discrimination of Cardiac Arrhythmias in Varied-Lead ECG Using ResNet-BiLSTM Network Activations'. Together they form a unique fingerprint.

Cite this