Arrhythmia Classification Using Higher Order Statistics

被引：0
|
作者：
Kutlu, Yakup [1 ]
Kuntalp, Damla [1 ]
Kuntalp, Mehmet [1 ]
机构：
[1] Dokuz Eylul Univ, Elekt & Elekt Muhendisligi Bolumu, Izmir, Turkey
来源：
2008 IEEE 16TH SIGNAL PROCESSING, COMMUNICATION AND APPLICATIONS CONFERENCE, VOLS 1 AND 2 | 2008年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this work, the features are extracted for the arrhythmia classification from the electrocardiograph (ECG) signals by using Higher order statistics. K-nearest neighborhood algorithm is used as classifier. Cumulants are calculated from the raw signals obtained from consecutive sample values of each R peak in ECG signals and used as features. In addition to these features, different features obtained from the relations of cumulants are also used. Simulation results shows that features obtained from the relations among cumulants are more discriminative than the cumulants.
引用
收藏
页码：733 / 736
页数：4
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