Universiti Teknologi Malaysia Institutional Repository

Characterization of ventricular arrhythmias in electrocardiogram signal using semantic mining algorithm

Sudirman, Rubita and Othman, Mohd. Afzan and Mat Safri, Norlaili (2010) Characterization of ventricular arrhythmias in electrocardiogram signal using semantic mining algorithm. In: 4th Asia International Conference on Mathematical Modelling & Computer Simulation (AMS 2010), 26-28 Mei 2010, Kota Kinabalu, Sabah.

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Official URL: http://dx.doi.org/10.1109/AMS.2010.68

Abstract

Ventricular arrhythmias, especially ventricular fibrillation, is a type of arrhythmias that can cause sudden death. The paper applies semantic mining approach to electrocardiograph (ECG) signals in order to extract its significant characteristics (frequency, damping coefficient and input signal) to be used for classification purpose. Real data from an arrhythmia database are used after noise filtration. After features extraction they are statistically classified into three groups, i.e. normal (N), normal patients (PN) and patients with ventricular arrhythmia (V). We found that the V, PN, and N types of ECG signals can be identified by the extracted parameters. It is estimated that the parameters in semantic algorithm can be use to predict the onset of ventricular arrhythmias.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:ECG, Semantic mining, heart diseases, life threatening arrhytmia prediction
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:23869
Deposited By: Liza Porijo
Deposited On:20 Sep 2012 08:19
Last Modified:20 Sep 2012 08:19

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