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العنوان
Automatic arrhythmia detection using support vector machine based on discrete wavelet transform /
الناشر
Ibrahim Hamed Ibrahim ,
المؤلف
Ibrahim Hamed Ibrahim
تاريخ النشر
2014
عدد الصفحات
99 P. :
الفهرس
يوجد فقط 14 صفحة متاحة للعرض العام

from 121

from 121

المستخلص

Arrhythmia is abnormality in the way electricity moves through the heart. The symptoms of arrhythmia are not present all the time; several examination hours of ECG records are needed. Even so, there is a high percentage of missing vital information. Automated arrhythmia detection of normal sinus rhythm and three types of arrhythmia (AF, VF, and SVT) was introduced by extracting the main features of the signal through DWT followed by PCA. These features were reduced through statistical analysis to be used as input to SVM that resulted in overall accuracy of 96.89%. The aim is to minimize the risk of missing vital information and to give physicians the confidence of making sound decisions with indistinct symptoms