Resources


Database Open Access

Influence of the MHD effect on 12-lead and 3-lead ECGs recorded in 1T to 7T MRI scanners

Johannes W Krug Passand

ECG signals were acquired in various MRI scanners to enable the study of the magnetohydrodynamic (MHD) effect. The MHD effect, which is caused by an interaction of the blood flow and the MRI’s high static magnetic field, superimposes the ECG signal.

ecg cardiac mri patient monitoring magnetohydrodynamic mri mhd

Published: May 18, 2021. Version: 1.0.0

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Challenge Open Access

Will Two Do? Varying Dimensions in Electrocardiography: the PhysioNet - Computing in Cardiology Challenge 2021

Matthew Reyna, Nadi Sadr, Annie Gu, Erick Andres Perez Alday, Chengyu Liu, Salman Seyedi, Amit Shah, Gari Clifford

Will Two Do? Varying Dimensions in Electrocardiography: the PhysioNet/Computing in Cardiology Challenge 2021

challenge classification multilead ecgs competition cardiac abnormalities

Published: Feb. 25, 2021. Version: 1.02


Database Open Access

Lobachevsky University Electrocardiography Database

Alena Kalyakulina, Igor Yusipov, Viktor Moskalenko, Alexander Nikolskiy, Konstantin Kosonogov, Nikolai Zolotykh, Mikhail Ivanchenko

ECG signal database that consists of 200 10-second 12-lead records. The boundaries and peaks of P, T waves and QRS complexes were manually annotated by cardiologists. Each record is annotated with the corresponding diagnosis.

diagnosis electrocardiography ecg database delineation open database

Published: Jan. 19, 2021. Version: 1.0.1

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Challenge Open Access

Improving the Quality of ECGs Collected using Mobile Phones - The PhysioNet Computing in Cardiology Challenge 2011

The aim of the PhysioNet/Computing in Cardiology Challenge 2011 is to develop an efficient algorithm able to run in near real-time within a mobile phone, that can provide useful feedback to a layperson in the process of acquiring a diagnostically us…

cellphone challenge ecg

Published: April 19, 2011. Version: 1.0.0


Database Open Access

PTB-XL, a large publicly available electrocardiography dataset

Patrick Wagner, Nils Strodthoff, Ralf-Dieter Bousseljot, Wojciech Samek, Tobias Schaeffter

The PTB-XL ECG dataset is a large dataset of 21837 clinical 12-lead ECGs from 18885 patients of 10 second length. The raw signal data has been annotated by up to two cardiologists with 71 different ECG statements and is supplemented by rich metadata.

ptb-xl ptb electrocardiography ecg

Published: April 24, 2020. Version: 1.0.1

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Challenge Open Access

Paroxysmal Atrial Fibrillation Events Detection from Dynamic ECG Recordings: The 4th China Physiological Signal Challenge 2021

Xingyao Wang, Caiyun Ma, Xiangyu Zhang, Hongxiang Gao, Gari Clifford, Chengyu Liu

CPSC2021 for paroxysmal atrial fibrillation events detection.

event detection paroxysmal atrial fibrillation

Published: June 21, 2021. Version: 1.0.0

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Database Open Access

Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB)

Lucie Maršánová, Andrea Nemcova, Radovan Smisek, Lukas Smital, Martin Vitek

BUT PDB is an ECG signal database with marked peaks of P waves created for the development, and objective comparison of P wave detection algorithms. The database consists of 50 2-minute 2-lead ECG signal records with various types of pathology.

ecg p wave

Published: Jan. 19, 2021. Version: 1.0.0

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Database Open Access

MIT-BIH Noise Stress Test Database

This database includes 12 half-hour ECG recordings and 3 half-hour recordings of noise typical in ambulatory ECG recordings. The noise recordings were made using physically active volunteers and standard ECG recorders, leads, and electrodes; the ele…

ecg noise

Published: Aug. 3, 1999. Version: 1.0.0

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Challenge Open Access

Classification of 12-lead ECGs: the PhysioNet - Computing in Cardiology Challenge 2020

Erick Andres Perez Alday, Annie Gu, Amit Shah, Chengyu Liu, Ashish Sharma, Salman Seyedi, Ali Bahrami Rad, Matthew Reyna, Gari Clifford

The goal of the 2020 PhysioNet - Computing in Cardiology Challenge is to design and implement a working, open-source algorithm that can automatically identify cardiac abnormalities in 12-lead ECG recordings.

Published: April 23, 2020. Version: 1.0.1


Database Open Access

Brno University of Technology ECG Quality Database (BUT QDB)

Andrea Nemcova, Radovan Smisek, Kamila Opravilová, Martin Vitek, Lukas Smital, Lucie Maršánová

The database is intended for the development and objective comparison of algorithms designed to assess the quality of ECG records. It also enables objective comparison of results between authors.

Published: July 22, 2020. Version: 1.0.0

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