支持向量机检测失神性癫痫发作

2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE) Pub Date : 2013-12-02 DOI:10.1109/ICEEE.2013.6676057

C. F. Reyes, T. J. Contreras, B. Tovar-Corona, L. Garay, M. A. Silva

{"title":"支持向量机检测失神性癫痫发作","authors":"C. F. Reyes, T. J. Contreras, B. Tovar-Corona, L. Garay, M. A. Silva","doi":"10.1109/ICEEE.2013.6676057","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":226547,"journal":{"name":"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Detection of absence epileptic seizures using support vector machine\",\"authors\":\"C. F. Reyes, T. J. Contreras, B. Tovar-Corona, L. Garay, M. A. Silva\",\"doi\":\"10.1109/ICEEE.2013.6676057\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":226547,\"journal\":{\"name\":\"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEEE.2013.6676057\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEE.2013.6676057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

应用支持向量机作为一种工具，在脑电图记录的事件检测从临床诊断为缺席癫痫患者。比较了五种核(线性、二次、多项式、RBP和MLP)对这种癫痫事件发生的检测效率。性能最好的核是二次核，在这种特定情况下准确率为99.43%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Detection of absence epileptic seizures using support vector machine

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

自引率

0.00%

发文量