Feature extraction of brain event-related potentials using cubic spline technique

M. A. Raheem, E. A. Hussein
{"title":"Feature extraction of brain event-related potentials using cubic spline technique","authors":"M. A. Raheem, E. A. Hussein","doi":"10.1109/AIC-MITCSA.2016.7759927","DOIUrl":null,"url":null,"abstract":"This paper illustrated the use of the Cubic spline Technique (CST) to analyze the EEG signals. It is provides full description of the extraction of the knots of EEG signals and then a discussion of how to select the optimum location of the knot and reducing the knots. Also the paper discussed that the feature extracted dependent on the optimal position of the knots. The initial results show the highest degree of accuracy to distinguish between five classes.","PeriodicalId":315179,"journal":{"name":"2016 Al-Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Al-Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIC-MITCSA.2016.7759927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper illustrated the use of the Cubic spline Technique (CST) to analyze the EEG signals. It is provides full description of the extraction of the knots of EEG signals and then a discussion of how to select the optimum location of the knot and reducing the knots. Also the paper discussed that the feature extracted dependent on the optimal position of the knots. The initial results show the highest degree of accuracy to distinguish between five classes.
基于三次样条技术的脑事件相关电位特征提取
本文阐述了利用三次样条技术(CST)分析脑电信号。详细介绍了脑电信号中脑结的提取,并对如何选择脑结的最佳位置和减少脑结进行了讨论。本文还讨论了特征的提取依赖于结点的最优位置。初步结果表明,在五个类别之间进行区分的准确率最高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信