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http://dx.doi.org/10.5391/JKIIS.2012.22.4.405

Abnormality Detection of ECG Signal by Rule-based Rhythm Classification  

Ryu, Chun-Ha (경북대학교 전자전기컴퓨터학부)
Kim, Sung-Oan (수원과학대학 컴퓨터정보과)
Kim, Se-Yun (삼성전자)
Kim, Tae-Hun (경북대학교 전자전기컴퓨터학부)
Choi, Byung-Jae (대구대학교 전자공학부)
Park, Kil-Houm (경북대학교 전자전기컴퓨터학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.22, no.4, 2012 , pp. 405-413 More about this Journal
Abstract
Low misclassification performance is significant with high classification accuracy for a reliable diagnosis of ECG signals, and diagnosing abnormal state as normal state can especially raises a deadly problem to a person in ECG test. In this paper, we propose detection and classification method of abnormal rhythm by rule-based rhythm classification reflecting clinical criteria for disease. Rule-based classification classifies rhythm types using rule-base for feature of rhythm section, and rule-base deduces decision results corresponding to professional materials of clinical and internal fields. Experimental results for the MIT-BIH arrhythmia database show that the applicability of proposed method is confirmed to classify rhythm types for normal sinus, paced, and various abnormal rhythms, especially without misclassification in detection aspect of abnormal rhythm.
Keywords
ECG Signal; Rule Base; Rhythm Classification; Abnormality Detection;
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Times Cited By KSCI : 3  (Citation Analysis)
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