从瞬态vep序列向时域SSVEP BCI范式模拟SSVEP的13指令BCI快速定标

M. A. Abbasi, A. Gaume, N. Francis, G. Dreyfus, F. Vialatte
{"title":"从瞬态vep序列向时域SSVEP BCI范式模拟SSVEP的13指令BCI快速定标","authors":"M. A. Abbasi, A. Gaume, N. Francis, G. Dreyfus, F. Vialatte","doi":"10.1109/NER.2015.7146591","DOIUrl":null,"url":null,"abstract":"A 13-command Brain-Computer Interface (BCI) based on Steady-State Visual Evoked Potentials (SSVEP) is assessed. The SSVEPs are simulated from VEP sequences recorded by electroencephalography (EEG) on the same subjects. SSVEP features extracted in the time domain are averaged over all channels of the occipital region. Most subjects achieved satisfactory classification rate (50~80% correct command detection). A simulated/offline information transfer rate of 60 bits/min is achieved, averaged across the best eight subjects. Online validation was performed on one new independent subject. The calibration procedure, based on VEP recordings, lasts one minute whatever the number of commands. Online information transfer rate of 58 bits/min is achieved.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Fast calibration of a thirteen-command BCI by simulating SSVEPs from trains of transient VEPs - towards time-domain SSVEP BCI paradigms\",\"authors\":\"M. A. Abbasi, A. Gaume, N. Francis, G. Dreyfus, F. Vialatte\",\"doi\":\"10.1109/NER.2015.7146591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A 13-command Brain-Computer Interface (BCI) based on Steady-State Visual Evoked Potentials (SSVEP) is assessed. The SSVEPs are simulated from VEP sequences recorded by electroencephalography (EEG) on the same subjects. SSVEP features extracted in the time domain are averaged over all channels of the occipital region. Most subjects achieved satisfactory classification rate (50~80% correct command detection). A simulated/offline information transfer rate of 60 bits/min is achieved, averaged across the best eight subjects. Online validation was performed on one new independent subject. The calibration procedure, based on VEP recordings, lasts one minute whatever the number of commands. Online information transfer rate of 58 bits/min is achieved.\",\"PeriodicalId\":137451,\"journal\":{\"name\":\"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NER.2015.7146591\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NER.2015.7146591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

对基于稳态视觉诱发电位(SSVEP)的13指令脑机接口(BCI)进行了评估。ssvep是根据同一受试者的脑电图记录的VEP序列来模拟的。在时域中提取的SSVEP特征在枕区所有通道上进行平均。大多数受试者的分类率满意(命令正确率为50~80%)。模拟/离线的信息传输速率达到60比特/分钟,在最好的8个科目中平均。在一个新的独立受试者上进行在线验证。校准过程,基于VEP记录,持续一分钟,无论命令的数量。在线信息传输速率可达58位/分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast calibration of a thirteen-command BCI by simulating SSVEPs from trains of transient VEPs - towards time-domain SSVEP BCI paradigms
A 13-command Brain-Computer Interface (BCI) based on Steady-State Visual Evoked Potentials (SSVEP) is assessed. The SSVEPs are simulated from VEP sequences recorded by electroencephalography (EEG) on the same subjects. SSVEP features extracted in the time domain are averaged over all channels of the occipital region. Most subjects achieved satisfactory classification rate (50~80% correct command detection). A simulated/offline information transfer rate of 60 bits/min is achieved, averaged across the best eight subjects. Online validation was performed on one new independent subject. The calibration procedure, based on VEP recordings, lasts one minute whatever the number of commands. Online information transfer rate of 58 bits/min is achieved.
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
×
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