A 12-lead Electrocardiogram Database for Arrhythmia Research Covering More Than 10,000 Patients

Authors

Jianwei Zhang, Chapman University
Jianming Zhang, Shaoxing People's Hospital
Sidy Daniako, Chapman University
Hai Yao, Zhejiang Cachet Jetboom Medical Devices CO.LTD
Hangyuan Guo, Shaoxing People's Hospital
Cyril Rakovski, Chapman UniversityFollow

Document Type

Article

Publication Date

2-12-2020

Abstract

This newly inaugurated research database for 12-lead electrocardiogram signals was created under the auspices of Chapman University and Shaoxing People’s Hospital (Shaoxing Hospital Zhejiang University School of Medicine) and aims to enable the scientific community in conducting new studies on arrhythmia and other cardiovascular conditions. Certain types of arrhythmias, such as atrial fibrillation, have a pronounced negative impact on public health, quality of life, and medical expenditures. As a non-invasive test, long term ECG monitoring is a major and vital diagnostic tool for detecting these conditions. This practice, however, generates large amounts of data, the analysis of which requires considerable time and effort by human experts. Advancement of modern machine learning and statistical tools can be trained on high quality, large data to achieve exceptional levels of automated diagnostic accuracy. Thus, we collected and disseminated this novel database that contains 12-lead ECGs of 10,646 patients with a 500 Hz sampling rate that features 11 common rhythms and 67 additional cardiovascular conditions, all labeled by professional experts. The dataset consists of 10-second, 12-dimension ECGs and labels for rhythms and other conditions for each subject. The dataset can be used to design, compare, and fine-tune new and classical statistical and machine learning techniques in studies focused on arrhythmia and other cardiovascular conditions.

Comments

This article was originally published in Scientific Data, volume 7, in 2020. https://doi.org/10.1038/s41597-020-0386-x

Recommended Citation

Zheng, J., Zhang, J., Danioko, S. et al. A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients. Sci Data 7, 48 (2020). https://doi.org/10.1038/s41597-020-0386-x

Peer Reviewed

1

Copyright

The authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.