A New Approach to Detect Epileptic Seizures in Electroencephalograms Using Teager Energy

C. Kamath
{"title":"A New Approach to Detect Epileptic Seizures in Electroencephalograms Using Teager Energy","authors":"C. Kamath","doi":"10.1155/2013/358108","DOIUrl":null,"url":null,"abstract":"A Teager energy (TE) based approach to discriminate electroencephalogram signals corresponding to nonseizure (eyes open, eyes closed, or interictal) and seizure (ictal) intervals is proposed. Though a good number of contributions have been made for seizure detection, the challenges of unbalanced data (nonseizure and seizure events) and system computational efficiency still remain a challenge. It is reported in the literature that the seizures are characterized by abnormal sudden discharges in the brain which get manifested in the EEG recordings by frequency changes and increased amplitudes. Teager energy (TE) is capable of tracking such rapid changes in frequency as well as amplitude in the time domain. An important finding of this study is that the mean TE quantifier is largely independent of the window length and exhibits relative consistency when used as a relative measure for comparison. We compared the diagnostic capability of TE quantifier with those of Higuchi’s fractal dimension and sample entropy in discriminating nonseizure and seizure states in the EEGs and found that TE outperforms the other two nonlinear quantifiers. The result shows that the application of this method compares favorably with conventional classification methods in terms of performance and is well suited for real-time automatic epileptic seizure detection.","PeriodicalId":93456,"journal":{"name":"ISRN biomedical engineering","volume":"2013 1","pages":"1-14"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2013/358108","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISRN biomedical engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2013/358108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

A Teager energy (TE) based approach to discriminate electroencephalogram signals corresponding to nonseizure (eyes open, eyes closed, or interictal) and seizure (ictal) intervals is proposed. Though a good number of contributions have been made for seizure detection, the challenges of unbalanced data (nonseizure and seizure events) and system computational efficiency still remain a challenge. It is reported in the literature that the seizures are characterized by abnormal sudden discharges in the brain which get manifested in the EEG recordings by frequency changes and increased amplitudes. Teager energy (TE) is capable of tracking such rapid changes in frequency as well as amplitude in the time domain. An important finding of this study is that the mean TE quantifier is largely independent of the window length and exhibits relative consistency when used as a relative measure for comparison. We compared the diagnostic capability of TE quantifier with those of Higuchi’s fractal dimension and sample entropy in discriminating nonseizure and seizure states in the EEGs and found that TE outperforms the other two nonlinear quantifiers. The result shows that the application of this method compares favorably with conventional classification methods in terms of performance and is well suited for real-time automatic epileptic seizure detection.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种利用青少年能量检测脑电图癫痫发作的新方法
提出了一种基于青少年能量(TE)的方法来区分非癫痫发作(睁眼、闭眼或间歇)和癫痫发作(间歇)间隔的脑电图信号。尽管在癫痫检测方面已经做出了很多贡献,但不平衡数据(非癫痫和癫痫事件)和系统计算效率的挑战仍然是一个挑战。文献报道癫痫发作的特点是脑内异常突然放电,在脑电图记录中表现为频率变化和幅度增加。Teager能量(TE)能够在时域内跟踪如此快速的频率和幅度变化。本研究的一个重要发现是,平均TE量词在很大程度上独立于窗口长度,并且在用作比较的相对度量时表现出相对一致性。我们将TE量词与Higuchi分形维数和样本熵的诊断能力在区分脑电图的非发作和发作状态方面进行了比较,发现TE量词优于其他两种非线性量词。结果表明,该方法在性能上优于传统的分类方法,适合于癫痫发作的实时自动检测。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Mathematical Methods in Biomedical Optics Optical Measurement of Blood Oxygen Saturation of Dental Pulp Slip Effects on Pulsatile Flow of Blood through a Stenosed Arterial Segment under Periodic Body Acceleration High-Fidelity Visualization of Large Medical Datasets on Commodity Hardware Companding Realizations of the Nonlinear Energy Operator
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1