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- W2183667907 abstract "Cardiac Arrhythmia is irregular heartbeat caused by irregular rhythms. The heartbeat is either slowed down or increased causing irregular rhythm. Electrocardiogram (ECG) is used to assess the heart arrhythmia. Different types of arrhythmia which are relevant to diagnosis of heart disease are accurately detected using ECG. Automatic assessment of arrhythmia from ECG is widely researched. Features in the form of RR interval extracted from the ECG and used for classifying the arrhythmia. In this paper, a new approach for cardiac arrhythmia classification is proposed. The proposed method incorporates Support Vector Machine (SVM) approach with Polynomial kernel and Radial Basis Function (RBF). First, the features are extracted from the time series ECG data using Discrete Cosine Transform (DCT) and the distance between RR wave computed. Experiments were conducted using MIT-BIH arrhythmia database." @default.
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- W2183667907 date "2012-01-01" @default.
- W2183667907 modified "2023-09-27" @default.
- W2183667907 title "Investigation of Support Vector Machine To Assess Cardiac Arrhythmia" @default.
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