基于期望的注视运动目标选择脑电标记

Darisy G. Zhao, A. Vasilyev, B. Kozyrskiy, Andrey V. Isachenko, Eugeny V. Melnichuk, B. Velichkovsky, S. Shishkin
{"title":"基于期望的注视运动目标选择脑电标记","authors":"Darisy G. Zhao, A. Vasilyev, B. Kozyrskiy, Andrey V. Isachenko, Eugeny V. Melnichuk, B. Velichkovsky, S. Shishkin","doi":"10.3217/978-3-85125-682-6-53","DOIUrl":null,"url":null,"abstract":"The use of an EEG expectation-related component, the expectancy wave (E-wave), in brainmachine interaction was proposed more than 50 years ago, but active exploration of this possibility has started only recently, in the context of developing passive brain-computer interfaces for the enhancement of gaze interaction. We report, for the first time, the results of a systematic experimental study that revealed an EEG marker for selecting intentionally an object among other moving objects using smooth pursuit eye movements. This marker appeared to have the same nature as the Ewave previously observed in the EEG accompanying the selection of static objects with gaze fixations. A convolutional neural network classified the intentional and spontaneous smooth pursuit eye movements with average ROC AUC 0.69±0.13 (M±SD). These results suggest that the E-wave might be robust enough to serve, after further improvement of the methodology, as the basis of hybrid eye-brain-computer interfaces applied for selection in dynamically changing visual environments.","PeriodicalId":433248,"journal":{"name":"Graz Brain-Computer Interface Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An expectation-based EEG marker for the selection of moving objects with gaze\",\"authors\":\"Darisy G. Zhao, A. Vasilyev, B. Kozyrskiy, Andrey V. Isachenko, Eugeny V. Melnichuk, B. Velichkovsky, S. Shishkin\",\"doi\":\"10.3217/978-3-85125-682-6-53\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of an EEG expectation-related component, the expectancy wave (E-wave), in brainmachine interaction was proposed more than 50 years ago, but active exploration of this possibility has started only recently, in the context of developing passive brain-computer interfaces for the enhancement of gaze interaction. We report, for the first time, the results of a systematic experimental study that revealed an EEG marker for selecting intentionally an object among other moving objects using smooth pursuit eye movements. This marker appeared to have the same nature as the Ewave previously observed in the EEG accompanying the selection of static objects with gaze fixations. A convolutional neural network classified the intentional and spontaneous smooth pursuit eye movements with average ROC AUC 0.69±0.13 (M±SD). These results suggest that the E-wave might be robust enough to serve, after further improvement of the methodology, as the basis of hybrid eye-brain-computer interfaces applied for selection in dynamically changing visual environments.\",\"PeriodicalId\":433248,\"journal\":{\"name\":\"Graz Brain-Computer Interface Conference\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Graz Brain-Computer Interface Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3217/978-3-85125-682-6-53\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Graz Brain-Computer Interface Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3217/978-3-85125-682-6-53","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

早在50多年前,人们就提出了在脑机交互中使用EEG期望相关成分,即期望波(E-wave),但对这种可能性的积极探索直到最近才开始,即在开发被动脑机接口以增强凝视交互的背景下。我们首次报道了一项系统实验研究的结果,该研究揭示了一种EEG标记,用于使用平滑的眼球运动在其他运动物体中有意识地选择一个物体。这个标记似乎与之前在EEG中观察到的Ewave具有相同的性质,伴随着凝视注视的静态物体的选择。卷积神经网络对有意和自发平滑追求眼动进行分类,平均ROC AUC为0.69±0.13 (M±SD)。这些结果表明,在进一步改进方法之后,e波可能足够强大,可以作为用于动态变化的视觉环境中选择的混合眼-脑-机接口的基础。
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 expectation-based EEG marker for the selection of moving objects with gaze
The use of an EEG expectation-related component, the expectancy wave (E-wave), in brainmachine interaction was proposed more than 50 years ago, but active exploration of this possibility has started only recently, in the context of developing passive brain-computer interfaces for the enhancement of gaze interaction. We report, for the first time, the results of a systematic experimental study that revealed an EEG marker for selecting intentionally an object among other moving objects using smooth pursuit eye movements. This marker appeared to have the same nature as the Ewave previously observed in the EEG accompanying the selection of static objects with gaze fixations. A convolutional neural network classified the intentional and spontaneous smooth pursuit eye movements with average ROC AUC 0.69±0.13 (M±SD). These results suggest that the E-wave might be robust enough to serve, after further improvement of the methodology, as the basis of hybrid eye-brain-computer interfaces applied for selection in dynamically changing visual environments.
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
Peanut: Personalised Emotional Agent for Neurotechnology User-Training Can Feature Selection be used to Detect Physiological Components in P300 based BCI for amyotrophic lateral Sclerosis patients? The effect of high and low frequencies in c-VEP BCI An expectation-based EEG marker for the selection of moving objects with gaze Utrecht neuroprosthesis System: New Features to Accommodate User Needs
×
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