A large scale 12-lead electrocardiogram database for arrhythmia study

This newly inaugurated research database for 12-lead electrocardiogram (ECG)
signals was created under the auspices of Chapman University, Shaoxing
People's Hospital (Shaoxing Hospital Zhejiang University School of Medicine),
and Ningbo First Hospital. It 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, ECG 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.
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 45,152 patients with a 500 Hz sampling rate that features multiple
common rhythms and additional cardiovascular conditions, all labeled by
professional experts. 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.