CCDD: AN ENHANCED STANDARD ECG DATABASE WITH ITS MANAGEMENT AND ANNOTATION TOOLS

Author:

ZHANG JIA-WEI12,LIU XIA3,DONG JUN2

Affiliation:

1. Software Engineering Institute, East China Normal University, Shanghai 200062, P. R. China

2. Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215123, P. R. China

3. Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, P. R. China

Abstract

Standard Electrocardiogram (ECG) database is created for validating and comparing different algorithms on feature detection and disease classification. At present, there are four frequently used standard databases: MIT-BIH arrhythmia database, QT database, CSE multi-lead database and AHA database. With the development in equipment and diagnosis approach, severe deficiencies are discovered and a new modern ECG database is needed for further research. So Chinese Cardiovascular Disease Database (CCDD or CCD database), which contains 12-Lead ECG data, detailed annotation features and beat diagnosis result is proposed. It is advanced for not only improving the raw ECG data's technical parameters, but also introducing valuable morphology features which are utilized by experienced cardiologists effectively. CCDD is employed by our group as well as aiming for supporting other research groups that work in automated ECG analysis.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Artificial Intelligence

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