ECG Classification

ECG classification aims to automatically diagnose cardiovascular conditions from electrocardiogram (ECG) signals, improving diagnostic speed and accuracy. Current research heavily utilizes deep learning, employing architectures like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers, often incorporating techniques to handle noise and artifacts, and improve robustness. These advancements hold significant promise for improving the efficiency and accessibility of cardiac diagnosis, particularly in resource-constrained settings or for early detection of life-threatening conditions like myocardial infarction.

Papers

October 9, 2024

rECGnition_v1.0: Arrhythmia detection using cardiologist-inspired multi-modal architecture incorporating demographic attributes in ECG
Shreya Srivastava, Durgesh Kumar, Jatin Bedi, Sandeep Seth, Deepak Sharma
Demographic Attribute Single Lead Electrocardiogram Data ECG Classification ECG Analysis MIT BIH Arrhythmia Arrhythmia Detection Multimodal Architecture

August 2, 2024

Non-linear Analysis Based ECG Classification of Cardiovascular Disorders
Suraj Kumar Behera, Debanjali Bhattacharya, Ninad Aithal, Neelam Sinha
ECG Classification Nonlinear Function Heart Disease Detection Recurrence Plot

May 8, 2024

ECG-SMART-NET: A Deep Learning Architecture for Precise ECG Diagnosis of Occlusion Myocardial Infarction
Nathan T. Riek, Murat Akcakaya, Zeineb Bouzid, Tanmay Gokhale, Stephanie Helman, Karina Kraevsky-Philips, Rui Qi Ji, Ervin Sejdic, Jessica K. Zègre-Hemsey, Christian Martin-Gill, Clifton W. Callaway, Samir Saba, Salah Al-Zaiti
Deep Learning Architecture ECG Classification Electrocardiogram Recording Electrocardiogram Diagnosis

April 26, 2024

Baseline Drift Tolerant Signal Encoding for ECG Classification with Deep Learning
Robert O Shea, Prabodh Katti, Bipin Rajendran
Deep Learning ECG Classification ECG Analysis Theoretical Peak Performance Analysis

August 31, 2023

Masked Transformer for Electrocardiogram Classification
Ya Zhou, Xiaolin Diao, Yanni Huo, Yang Liu, Xiaohan Fan, Wei Zhao
Electrocardiogram Data Electrocardiogram Classification ECG Classification Lightweight Transformer Masked Transformer

August 24, 2023

Optimizing Neural Network Scale for ECG Classification
Byeong Tak Lee, Yong-Yeon Jo, Joon-Myoung Kwon
Neural Network Convolutional Neural Network Residual Neural Network ECG Classification ECG Analysis

July 25, 2023

ECG classification using Deep CNN and Gramian Angular Field
Youssef Elmir, Yassine Himeur, Abbes Amira
Convolutional Neural Network Feature Representation ECG Signal ECG Classification ECG Analysis Gramian Angular Field

June 2, 2023

Transforming ECG Diagnosis:An In-depth Review of Transformer-based DeepLearning Models in Cardiovascular Disease Detection
Zibin Zhao
Deep Learning Transformer Architecture Transformer Based Model Comprehensive Review State of the Art Deep Transformer Based Deep ECG Classification ECG Analysis Cardiovascular Disease Detection

March 6, 2023

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN
Md Shofiqul Islam, Khondokar Fida Hasan, Sunjida Sultana, Shahadat Uddin, Pietro Lio, Julian M. W. Quinn, Mohammad Ali Moni
Gated Recurrent Unit Hierarchical Attention ECG Signal ECG Classification Dilated Convolutional Neural Network Attention Based Bidirectional

January 28, 2023

MVKT-ECG: Efficient Single-lead ECG Classification on Multi-Label Arrhythmia by Multi-View Knowledge Transferring
Yuzhen Qin, Li Sun, Hui Chen, Wei-qiang Zhang, Wenming Yang, Jintao Fei, Guijin Wang
High Efficiency Multi Label Single Lead Electrocardiogram Data Lead ECG ECG Classification Multi Disease

November 23, 2022

A Dual-scale Lead-seperated Transformer With Lead-orthogonal Attention And Meta-information For Ecg Classification
Yang Li, Guijin Wang, Zhourui Xia, Wenming Yang, Li Sun
Cross Attention Metadata Information Single Lead Electrocardiogram Data ECG Classification Orthogonal Attention

November 14, 2022

Advancing the State-of-the-Art for ECG Analysis through Structured State Space Models
Temesgen Mehari, Nils Strodthoff
State of the Art State Space Model Convolutional Architecture ECG Classification Electrocardiogram Representation ECG Analysis

November 3, 2022

Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria
Theresa Bender, Jacqueline Michelle Beinecke, Dagmar Krefting, Carolin Müller, Henning Dathe, Tim Seidler, Nicolai Spicher, Anne-Christin Hauschild
Deep Neural Network Deep Learning Model General Analysis Feature Wise Attribution Method ECG Classification Pre Trained Deep Neural Network

October 31, 2022

SEVGGNet-LSTM: a fused deep learning model for ECG classification
Tongyue He, Yiming Chen, Junxin Chen, Wei Wang, Yicong Zhou
Deep Learning Model Recurrent Neural Network Deep Learning Algorithm ECG Classification

October 5, 2022

Two-stream Network for ECG Signal Classification
Xinyao Hou, Shengmei Qin, Jianbo Su
Electrocardiogram Signal Electrocardiogram Data Electrocardiogram Classification ECG Classification Stream Network MIT BIH Arrhythmia

August 25, 2022

Deep Learning-based ECG Classification on Raspberry PI using a Tensorflow Lite Model based on PTB-XL Dataset
Kushagra Sharma, Rasit Eskicioglu
Machine Learning Model Internet of Thing Device Electrocardiogram Classification ECG Classification Raspberry Pi TXL PBC Dataset Tensorflow Lite

July 25, 2022

LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification
Khiem H. Le, Hieu H. Pham, Thao BT. Nguyen, Tu A. Nguyen, Tien N. Thanh, Cuong D. Do
Lightweight High Lead ECG ECG Classification Canine Electrocardiogram Explainable Deep Learning 12 Lead

July 19, 2022

Decorrelative Network Architecture for Robust Electrocardiogram Classification
Christopher Wiedeman, Ge Wang
Adversarial Attack Adversarial Sample Feature Decorrelation ECG Classification Novel Ensemble Bayesian Deep Bayesian Ensemble

May 12, 2022

Evolving SimGANs to Improve Abnormal Electrocardiogram Classification
Gabriel Wang, Anish Thite, Rodd Talebi, Anthony D'Achille, Alex Mussa, Jason Zutty
Generative Adversarial Network ECG Classification Semantic Evolution GAN

April 8, 2022

ECG Biometric Recognition: Review, System Proposal, and Benchmark Evaluation
Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez
Narrative Review Evaluation Benchmark Proposal Balance Refinement Single Lead Electrocardiogram Data Biometric Recognition Lead ECG ECG Classification Electrocardiogram Recording

ECG Classification

Papers

rECGnition_v1.0: Arrhythmia detection using cardiologist-inspired multi-modal architecture incorporating demographic attributes in ECG

Non-linear Analysis Based ECG Classification of Cardiovascular Disorders

ECG-SMART-NET: A Deep Learning Architecture for Precise ECG Diagnosis of Occlusion Myocardial Infarction

Baseline Drift Tolerant Signal Encoding for ECG Classification with Deep Learning

Masked Transformer for Electrocardiogram Classification

Optimizing Neural Network Scale for ECG Classification

ECG classification using Deep CNN and Gramian Angular Field

Transforming ECG Diagnosis:An In-depth Review of Transformer-based DeepLearning Models in Cardiovascular Disease Detection

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN

MVKT-ECG: Efficient Single-lead ECG Classification on Multi-Label Arrhythmia by Multi-View Knowledge Transferring

A Dual-scale Lead-seperated Transformer With Lead-orthogonal Attention And Meta-information For Ecg Classification

Advancing the State-of-the-Art for ECG Analysis through Structured State Space Models

Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria

SEVGGNet-LSTM: a fused deep learning model for ECG classification

Two-stream Network for ECG Signal Classification

Deep Learning-based ECG Classification on Raspberry PI using a Tensorflow Lite Model based on PTB-XL Dataset

LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification

Decorrelative Network Architecture for Robust Electrocardiogram Classification

Evolving SimGANs to Improve Abnormal Electrocardiogram Classification

ECG Biometric Recognition: Review, System Proposal, and Benchmark Evaluation