Health & Environmental Research Online (HERO)


Print Feedback Export to File
7117359 
Journal Article 
CCDD: AN ENHANCED STANDARD ECG DATABASE WITH ITS MANAGEMENT AND ANNOTATION TOOLS 
Zhang Jia-Wei; Liu Xia; Dong Jun; , 
2012 
Yes 
International Journal on Artificial Intelligence Tools
ISSN: 0218-2130 
WORLD SCIENTIFIC PUBL CO PTE LTD 
SINGAPORE 
WOS:000310637200002 
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.