• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

从脑电图中去除眼部伪迹——一种眼电图的生物物理方法。

Removal of ocular artifacts from the EEG--a biophysical approach to the EOG.

作者信息

Elbert T, Lutzenberger W, Rockstroh B, Birbaumer N

出版信息

Electroencephalogr Clin Neurophysiol. 1985 May;60(5):455-63. doi: 10.1016/0013-4694(85)91020-x.

DOI:10.1016/0013-4694(85)91020-x
PMID:2580697
Abstract

The present paper describes the propagation of ocular potentials across the scalp on a biophysical basis. It is concluded that 3 EOG derivations (two for EEG records along the midline) are generally necessary to account for ocular disturbances in the EEG. The inadequacy of many methods suggested for EOG artifact control may be due to the false assumption that just one EOG derivation provides enough information to remove ocular potentials from any EEG recording along the mid(-sagittal) line. A comparison of compensation with one or with two EOG derivations is described for a data set of slow brain potentials. A frequency dependence of the ocular influence cannot be neglected, if fast and slow EOG activities have to be removed. The present considerations should allow a more theoretically based decision of the EOG correction method necessary for a certain data set.

摘要

本文基于生物物理学原理描述了眼电位在头皮上的传播。得出的结论是,一般需要3个眼电图(EOG)导联(其中两个用于沿中线记录脑电图)来解释脑电图中的眼电干扰。许多针对EOG伪迹控制所建议方法的不足之处,可能是由于错误地假设仅一个EOG导联就能提供足够信息,以从沿中(矢状)线的任何脑电图记录中去除眼电位。针对一组慢脑电位数据集,描述了使用一个或两个EOG导联进行补偿的比较情况。如果要去除快速和慢速EOG活动,眼电影响的频率依赖性不可忽视。目前的考虑应有助于基于理论对特定数据集所需的EOG校正方法做出更合理的决策。

相似文献

1
Removal of ocular artifacts from the EEG--a biophysical approach to the EOG.从脑电图中去除眼部伪迹——一种眼电图的生物物理方法。
Electroencephalogr Clin Neurophysiol. 1985 May;60(5):455-63. doi: 10.1016/0013-4694(85)91020-x.
2
Quantitative evaluation of ocular artifact removal methods based on real and estimated EOG signals.基于真实和估计眼电信号的眼动伪迹去除方法的定量评估。
Annu Int Conf IEEE Eng Med Biol Soc. 2008;2008:5041-4. doi: 10.1109/IEMBS.2008.4650346.
3
Removal of ocular artifact from the EEG: a review.从脑电图中去除眼部伪迹:综述
Neurophysiol Clin. 2000 Feb;30(1):5-19. doi: 10.1016/S0987-7053(00)00055-1.
4
The removal of the eye-movement artifact from the EEG by regression analysis in the frequency domain.通过频域回归分析从脑电图中去除眼动伪迹。
Biol Psychol. 1983 Feb-Mar;16(1-2):127-47. doi: 10.1016/0301-0511(83)90059-5.
5
[Procedures for on-line minimizing of eyelid and vertical eye movement artefacts in the EEG].[脑电图中在线最小化眼睑和垂直眼球运动伪迹的程序]
EEG EMG Z Elektroenzephalogr Elektromyogr Verwandte Geb. 1988 Jun;19(2):96-100.
6
A new method for off-line removal of ocular artifact.一种用于离线去除眼电伪迹的新方法。
Electroencephalogr Clin Neurophysiol. 1983 Apr;55(4):468-84. doi: 10.1016/0013-4694(83)90135-9.
7
Removal of the ocular artifacts from EEG data using a cascaded spatio-temporal processing.使用级联时空处理从脑电图数据中去除眼部伪迹。
Comput Methods Programs Biomed. 2006 Aug;83(2):95-103. doi: 10.1016/j.cmpb.2006.03.009. Epub 2006 Aug 1.
8
Ocular artifacts in children's EEG: selection is better than correction.儿童脑电图中的眼部伪迹:选择优于校正。
Biol Psychol. 1998 Aug;48(3):281-300. doi: 10.1016/s0301-0511(98)00041-6.
9
Removal of ocular artifacts from electro-encephalogram by adaptive filtering.通过自适应滤波去除脑电图中的眼部伪迹。
Med Biol Eng Comput. 2004 May;42(3):407-12. doi: 10.1007/BF02344717.
10
Ballistocardiogram artifact removal from EEG signals using adaptive filtering of EOG signals.利用眼电信号的自适应滤波从脑电图信号中去除心冲击图伪迹。
Physiol Meas. 2006 Nov;27(11):1227-40. doi: 10.1088/0967-3334/27/11/014. Epub 2006 Sep 29.

引用本文的文献

1
DHCT-GAN: Improving EEG Signal Quality with a Dual-Branch Hybrid CNN-Transformer Network.DHCT-GAN:使用双分支混合卷积神经网络-Transformer网络提高脑电图信号质量
Sensors (Basel). 2025 Jan 3;25(1):231. doi: 10.3390/s25010231.
2
The impact of electrode selection for ocular correction on the reward positivity and late positive potential components in adolescents.电极选择对青少年眼矫正的奖赏正波和晚正电位成分的影响。
Psychophysiology. 2024 Mar;61(3):e14497. doi: 10.1111/psyp.14497. Epub 2023 Dec 4.
3
Causal roles of prefrontal cortex during spontaneous perceptual switching are determined by brain state dynamics.
前额叶皮层在自发知觉转换过程中的因果作用取决于大脑状态动力学。
Elife. 2021 Oct 29;10:e69079. doi: 10.7554/eLife.69079.
4
A Recent Investigation on Detection and Classification of Epileptic Seizure Techniques Using EEG Signal.近期关于使用脑电图信号的癫痫发作检测与分类技术的研究
Brain Sci. 2021 May 20;11(5):668. doi: 10.3390/brainsci11050668.
5
Neural precursors of decisions that matter-an ERP study of deliberate and arbitrary choice.决策的神经前体——有意和任意选择的 ERP 研究。
Elife. 2019 Oct 23;8:e39787. doi: 10.7554/eLife.39787.
6
Learning Desire Is Predicted by Similar Neural Processing of Naturalistic Educational Materials.学习欲望由自然主义教育材料的相似神经处理预测。
eNeuro. 2019 Oct 3;6(5). doi: 10.1523/ENEURO.0083-19.2019. Print 2019 Sep/Oct.
7
Format change and semantic relatedness effects on the ERP correlates of recognition: old pairs, new pairs, different stories.格式变化和语义相关性对识别的事件相关电位相关性的影响:旧对、新对、不同故事。
Exp Brain Res. 2017 Apr;235(4):1007-1019. doi: 10.1007/s00221-016-4859-2. Epub 2016 Dec 28.
8
A semi-simulated EEG/EOG dataset for the comparison of EOG artifact rejection techniques.用于比较眼电伪迹去除技术的半模拟脑电图/眼电图数据集。
Data Brief. 2016 Jun 29;8:1004-6. doi: 10.1016/j.dib.2016.06.032. eCollection 2016 Sep.
9
Hybrid ICA-Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals.混合独立成分分析-回归:从脑电图信号中自动识别和去除眼电伪迹
Front Hum Neurosci. 2016 May 3;10:193. doi: 10.3389/fnhum.2016.00193. eCollection 2016.
10
Characterization of Artifacts Produced by Gel Displacement on Non-invasive Brain-Machine Interfaces during Ambulation.行走过程中非侵入性脑机接口上凝胶移位产生的伪迹特征
Front Neurosci. 2016 Feb 25;10:60. doi: 10.3389/fnins.2016.00060. eCollection 2016.