Empirical mode decomposition based support vector machines for microemboli classification

K. Ferroudji, N. Benoudjit, Ayache Bouakaz
{"title":"Empirical mode decomposition based support vector machines for microemboli classification","authors":"K. Ferroudji, N. Benoudjit, Ayache Bouakaz","doi":"10.1109/WOSSPA.2013.6602341","DOIUrl":null,"url":null,"abstract":"The classification of circulating microemboli, in the bloodstream, as gaseous or particulate matter is vital for selecting appropriate treatment for patients. Until now, Doppler techniques have shown some limitations to determine clearly the nature of circulating microemboli. The traditional techniques are largely based on the Fourier analysis. In this paper we present new emboli detection method based on Empirical mode decomposition and support vector machine using Radio Frequency (RF) signal instead of Doppler signals.","PeriodicalId":417940,"journal":{"name":"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOSSPA.2013.6602341","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

The classification of circulating microemboli, in the bloodstream, as gaseous or particulate matter is vital for selecting appropriate treatment for patients. Until now, Doppler techniques have shown some limitations to determine clearly the nature of circulating microemboli. The traditional techniques are largely based on the Fourier analysis. In this paper we present new emboli detection method based on Empirical mode decomposition and support vector machine using Radio Frequency (RF) signal instead of Doppler signals.
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
基于经验模态分解的支持向量机微栓子分类
将血液中循环的微栓子分类为气体或颗粒物质对于为患者选择适当的治疗方法至关重要。到目前为止,多普勒技术在明确确定循环微栓子的性质方面显示出一些局限性。传统的技术主要是基于傅里叶分析。本文提出了一种基于经验模态分解和支持向量机的新型栓子检测方法,采用射频信号代替多普勒信号。
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
Tensor estimation and visualization using dMRI Effect of multi-users and multipaths on the performance of an adaptive serial acquisition scheme for DS/CDMA systems Relay self interference minimisation using tapped filter New procedure in designing 2D-IIR filters based on 2D-FIR filters approximation Empirical mode decomposition based support vector machines for microemboli classification
×
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