Neuroelectrical source imaging of mu rhythm control for BCI applications.

M Mattiocco, F Babiloni, D Mattia, S Bufalari, S Sergio, S Salinari, M G Marciani, F Cincotti
{"title":"Neuroelectrical source imaging of mu rhythm control for BCI applications.","authors":"M Mattiocco,&nbsp;F Babiloni,&nbsp;D Mattia,&nbsp;S Bufalari,&nbsp;S Sergio,&nbsp;S Salinari,&nbsp;M G Marciani,&nbsp;F Cincotti","doi":"10.1109/IEMBS.2006.260128","DOIUrl":null,"url":null,"abstract":"<p><p>In the last decade, the possibility to noninvasively estimate cortical activity has been highlighted by the application of the techniques known as high resolution EEG. These techniques include a subject's multi-compartment head model (scalp, skull, dura mater, cortex) constructed from individual magnetic resonance images, multi-dipole source model, and regularized linear inverse source estimates of cortical current density. The aim of this paper is to demonstrate that the use of cortical activity estimated from noninvasive EEG recordings of motor imagery is useful in the context of a brain computer interface as compared with others scalp spatial filters usually used on-line.</p>","PeriodicalId":72689,"journal":{"name":"Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference","volume":" ","pages":"980-3"},"PeriodicalIF":0.0000,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/IEMBS.2006.260128","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.2006.260128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

In the last decade, the possibility to noninvasively estimate cortical activity has been highlighted by the application of the techniques known as high resolution EEG. These techniques include a subject's multi-compartment head model (scalp, skull, dura mater, cortex) constructed from individual magnetic resonance images, multi-dipole source model, and regularized linear inverse source estimates of cortical current density. The aim of this paper is to demonstrate that the use of cortical activity estimated from noninvasive EEG recordings of motor imagery is useful in the context of a brain computer interface as compared with others scalp spatial filters usually used on-line.

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
脑机接口中mu节律控制的神经电源成像。
在过去的十年中,由于高分辨率脑电图技术的应用,无创估计皮层活动的可能性得到了强调。这些技术包括由单个磁共振图像构建的受试者多室头部模型(头皮、颅骨、硬脑膜、皮层)、多偶极子源模型和皮层电流密度的正则化线性逆源估计。本文的目的是证明,与通常在线使用的其他头皮空间过滤器相比,使用从运动图像的无创脑电图记录中估计的皮层活动在脑机接口的背景下是有用的。
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
CiteScore
2.20
自引率
0.00%
发文量
0
期刊最新文献
Rapid Label-free DNA Quantification by Multi-frequency Impedance Sensing on a Chip. A Comparison of 1-D and 2-D Deep Convolutional Neural Networks in ECG Classification Brain Morphometry Analysis with Surface Foliation Theory Low-Cost, USB Connected and Multi-Purpose Biopotential Recording System. A Fast Respiratory Rate Estimation Method using Joint Sparse Signal Reconstruction based on Regularized Sparsity Adaptive Matching Pursuit.
×
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