SSVEP-Based BCIs

R. Singla
{"title":"SSVEP-Based BCIs","authors":"R. Singla","doi":"10.5772/INTECHOPEN.75693","DOIUrl":null,"url":null,"abstract":"This chapter describes the method of flickering targets, eliciting fundamental frequency changes in the EEG signal of the subject, used to drive machine commands after interpretation of user’s intentions. The steady-state response of the changes in the EEG caused by events such as visual stimulus applied to the subject via a computer screen is called steady-state visually evoked potential (SSVEP). This feature of the EEG signal can be used to form a basis of input to assistive devices for locked in patients to improve their quality of life, as well as for performance enhancing devices for healthy subjects. The contents of this chapter describe the SSVEP stimuli; feature extraction techniques, feature classification techniques and a few applications based on SSVEP based BCI.","PeriodicalId":448864,"journal":{"name":"Evolving BCI Therapy - Engaging Brain State Dynamics","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evolving BCI Therapy - Engaging Brain State Dynamics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/INTECHOPEN.75693","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

This chapter describes the method of flickering targets, eliciting fundamental frequency changes in the EEG signal of the subject, used to drive machine commands after interpretation of user’s intentions. The steady-state response of the changes in the EEG caused by events such as visual stimulus applied to the subject via a computer screen is called steady-state visually evoked potential (SSVEP). This feature of the EEG signal can be used to form a basis of input to assistive devices for locked in patients to improve their quality of life, as well as for performance enhancing devices for healthy subjects. The contents of this chapter describe the SSVEP stimuli; feature extraction techniques, feature classification techniques and a few applications based on SSVEP based BCI.
SSVEP-Based好像
本章描述了闪烁目标的方法,在被试的脑电图信号中引出基频变化,在解读用户意图后驱动机器指令。稳态视觉诱发电位(SSVEP)是通过计算机屏幕对被试施加视觉刺激等事件引起的脑电图变化的稳态反应。脑电图信号的这一特征可以作为锁定患者辅助装置的输入基础,以提高患者的生活质量,也可以作为健康受试者的性能增强装置的输入基础。本章的内容描述了SSVEP刺激;特征提取技术、特征分类技术以及基于SSVEP的脑机接口的一些应用。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信