ISCAS OpenIR
ccdd: an enhanced standard ecg database with its management and annotation tools
Zhang Jia-Wei; Liu Xia; Dong Jun
2012
会议录名称International Journal on Artificial Intelligence Tools
页码-
收录类别EI
ISSN0218-2130
部门归属(1) Software Engineering Institute East China Normal University Shanghai 200062 China; (2) Rui Jin Hospital Shanghai Jiao Tong University School of Medicine Shanghai 200025 China; (3) Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of Sciences Suzhou 215123 China
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. © 2012 World Scientific Publishing Company.; 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. © 2012 World Scientific Publishing Company.
关键词Diagnosis Diseases Electrocardiography Morphology
语种英语
内容类型会议论文
URI标识http://ir.iscas.ac.cn/handle/311060/15969
专题中国科学院软件研究所
推荐引用方式
GB/T 7714
Zhang Jia-Wei,Liu Xia,Dong Jun. ccdd: an enhanced standard ecg database with its management and annotation tools[C],2012:-.
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