Detection of Absence Epileptic Seizures Using Support Vector Machine

被引：0
|
作者：
Reyes, C. F. [1 ]
Contreras, T. J. [1 ]
Tovar, B. [2 ]
Garay, L. I. [1 ]
Silva, M. A. [3 ]
机构：
[1] IPN, UPIITA, Maestria Tecnol Avanzada, Mexico City, DF, Mexico
[2] IPN, UPIITA, Acad Sistemas, Mexico City, DF, Mexico
[3] IMSS, Hosp La Raza, Mexico City, DF, Mexico
来源：
2013 10TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, COMPUTING SCIENCE AND AUTOMATIC CONTROL (CCE) | 2013年
关键词：
EEG; epilepsy; kernels; SVM; DIAGNOSIS; EEG;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An application of support vector machine is presented as a tool for events detection in the electroencephalogram recorded from a patient clinically diagnosed with absence epilepsy. A comparison of five kernels is shown (linear, quadratic, polynomial, RBP and MLP) evaluating their efficiency for the detection of this epileptic event occurrence. The kernel with the best performance is the quadratic, with 99.43% accuracy in this specific case.
引用
收藏
页码：132 / 137
页数：6
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