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

被引:37
作者
Zhang Jia-Wei [1 ,3 ]
Liu Xia [2 ]
Dong Jun [1 ]
机构
[1] Chinese Acad Sci, Suzhou Inst Nanotech & Nanobion, Suzhou 215123, Peoples R China
[2] Shanghai Jiao Tong Univ, Rui Jin Hosp, Sch Med, Shanghai 200025, Peoples R China
[3] E China Normal Univ, Inst Software Engn, Shanghai 200062, Peoples R China
关键词
ECG; standard ECG database; feature annotation; morphology features; QRS pattern; HEARTBEAT INTERVAL FEATURES; CLASSIFICATION; MORPHOLOGY;
D O I
10.1142/S0218213012400209
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页数:26
相关论文
共 27 条
[1]  
[Anonymous], 2011, AHA DATABASE DVD
[2]  
[Anonymous], 2011, AHA DATABASE
[3]  
[Anonymous], 2011, 12 LEAD ECG MONITOR
[4]  
[Anonymous], 2011, PRB DIAGNOSTIC ECG D
[5]  
[Anonymous], 2011, MIT BIH ARRHYTHMIA D
[6]  
[Anonymous], 2011, NATL CARDIOVASCULAR
[7]  
[Anonymous], P COMPUT CARDIOL
[8]  
Bruce Foster D, 2009, 12 LEAD ELECTROCARDI, P9
[9]   A novel approach for classification of ECG arrhythmias: Type-2 fuzzy clustering neural network [J].
Ceylan, Rahime ;
Ozbay, Yuksel ;
Karlik, Bekir .
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (03) :6721-6726
[10]   Automatic classification of heartbeats using ECG morphology and heartbeat interval features [J].
de Chazal, P ;
O'Dwyer, M ;
Reilly, RB .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2004, 51 (07) :1196-1206