ISCAS OpenIR
ccdd: an enhanced standard ecg database with its management and annotation tools
Zhang Jia-Wei; Liu Xia; Dong Jun
2012
SourceInternational Journal on Artificial Intelligence Tools
Pages-
Indexed TypeEI
ISSN0218-2130
Department(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
English AbstractStandard 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.
KeywordDiagnosis Diseases Electrocardiography Morphology
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/15969
Collection中国科学院软件研究所
Recommended Citation
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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