一种基于EMD的呼吸暂停和正常脑电图信号识别方法

S. Yadav, V. Bajaj, Anil Kumar
{"title":"一种基于EMD的呼吸暂停和正常脑电图信号识别方法","authors":"S. Yadav, V. Bajaj, Anil Kumar","doi":"10.1109/RISE.2017.8378152","DOIUrl":null,"url":null,"abstract":"Sleep apnea is a type of sleep syndrome and is caused due to breaks or pause during sleep. A new technique is used in this paper for the discrimination between apnea and normal sleep electroencephalogram (EEG) signals. Here, the empirical mode decomposition (EMD) method is used for the discrimination purpose of apnea and normal sleep EEG signals. In EMD method, EEG signal (which may be non-linear or non-stationary in nature) has been decomposed into oscillatory functions known as intrinsic mode functions (IMFs). After decomposition of EEG signals, two important features termed as energy and entropy has been extracted. These features help in discrimination process of EEG signals.","PeriodicalId":166244,"journal":{"name":"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An EMD based approach for discrimination of apnea and normal EEG signals\",\"authors\":\"S. Yadav, V. Bajaj, Anil Kumar\",\"doi\":\"10.1109/RISE.2017.8378152\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sleep apnea is a type of sleep syndrome and is caused due to breaks or pause during sleep. A new technique is used in this paper for the discrimination between apnea and normal sleep electroencephalogram (EEG) signals. Here, the empirical mode decomposition (EMD) method is used for the discrimination purpose of apnea and normal sleep EEG signals. In EMD method, EEG signal (which may be non-linear or non-stationary in nature) has been decomposed into oscillatory functions known as intrinsic mode functions (IMFs). After decomposition of EEG signals, two important features termed as energy and entropy has been extracted. These features help in discrimination process of EEG signals.\",\"PeriodicalId\":166244,\"journal\":{\"name\":\"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RISE.2017.8378152\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RISE.2017.8378152","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

睡眠呼吸暂停是一种睡眠综合症,是由于睡眠中断或暂停引起的。本文提出了一种新的识别呼吸暂停和正常睡眠脑电图信号的方法。本文采用经验模态分解(EMD)方法对呼吸暂停和正常睡眠脑电图信号进行判别。在EMD方法中,脑电信号(本质上可能是非线性或非平稳的)被分解成振荡函数,称为本征模态函数(IMFs)。对脑电信号进行分解后,提取出能量和熵两个重要特征。这些特征有助于脑电信号的识别处理。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An EMD based approach for discrimination of apnea and normal EEG signals
Sleep apnea is a type of sleep syndrome and is caused due to breaks or pause during sleep. A new technique is used in this paper for the discrimination between apnea and normal sleep electroencephalogram (EEG) signals. Here, the empirical mode decomposition (EMD) method is used for the discrimination purpose of apnea and normal sleep EEG signals. In EMD method, EEG signal (which may be non-linear or non-stationary in nature) has been decomposed into oscillatory functions known as intrinsic mode functions (IMFs). After decomposition of EEG signals, two important features termed as energy and entropy has been extracted. These features help in discrimination process of EEG signals.
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
自引率
0.00%
发文量
0
期刊最新文献
Copyright page Cuffless blood pressure monitoring using PTT and PWV methods Estimating vital signs through non-contact video-based approaches: A survey Feedback particle filter based image denoiser WCA based re-clustering approach in DSR and OLSR routing protocols in MANET
×
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