TIIS (한국인터넷정보학회)
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| 한글제목(Korean Title) |
Classification of Premature Ventricular Contraction using Error Back-Propagation |
| 영문제목(English Title) |
Classification of Premature Ventricular Contraction using Error Back-Propagation |
| 저자(Author) |
Eunkwang Jeon
Bong-Keun Jung
Yunyoung Nam
HwaMin Lee
Eunkwang Jeon
Bong-Keun Jung
Yunyoung Nam
HwaMin Lee
|
| 원문수록처(Citation) |
VOL 12 NO. 02 PP. 0988 ~ 1001 (2018. 02) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Arrhythmia has recently emerged as one of the major causes of death in Koreans. Premature Ventricular Contraction (PVC) is the most common arrhythmia that can be found in clinical practice, and it may be a precursor to dangerous arrhythmias, such as paroxysmal insomnia, ventricular fibrillation, and coronary artery disease. Therefore, we need for a method that can detect an abnormal heart beat and diagnose arrhythmia early. We extracted the features corresponding to the QRS pattern from the subject's ECG signal and classify the premature ventricular contraction waveform using the features. We modified the weighting and bias values based on the error back-propagation algorithm through learning data. We classify the normal signal and the premature ventricular contraction signal through the modified weights and deflection values. MIT-BIH arrhythmia data sets were used for performance tests. We used RR interval, QS interval, QR amplitude and RS amplitude features. And the hidden layer with two nodes is composed of two layers to form a total three layers (input layer 0, output layer 3). |
| 키워드(Keyword) |
ARRHYTHMIA
BACK-PROPAGATION
PREMATURE VENTRICULAR CONTRACTION
ARRHYTHMIA
BACK-PROPAGATION
PREMATURE VENTRICULAR CONTRACTION
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