Navigation in virtual and real environment using brain computer interface:a progress report

Q1 Computer Science Virtual Reality Intelligent Hardware Pub Date : 2022-04-01 DOI:10.1016/j.vrih.2021.10.002
Haochen Hu , Yue Liu , Kang Yue , Yongtian Wang
{"title":"Navigation in virtual and real environment using brain computer interface:a progress report","authors":"Haochen Hu ,&nbsp;Yue Liu ,&nbsp;Kang Yue ,&nbsp;Yongtian Wang","doi":"10.1016/j.vrih.2021.10.002","DOIUrl":null,"url":null,"abstract":"<div><p>A brain-computer interface (BCI) facilitates bypassing the peripheral nervous system and directly communicating with surrounding devices. Navigation technology using BCI has developed—from exploring the prototype paradigm in the virtual environment (VE) to accurately completing the locomotion intention of the operator in the form of a powered wheelchair or mobile robot in a real environment. This paper summarizes BCI navigation applications that have been used in both real and VEs in the past 20 years. Horizontal comparisons were conducted between various paradigms applied to BCI and their unique signal-processing methods. Owing to the shift in the control mode from synchronous to asynchronous, the development trend of navigation applications in the VE was also reviewed. The contrast between highlevel commands and low-level commands is introduced as the main line to review the two major applications of BCI navigation in real environments: mobile robots and unmanned aerial vehicles (UAVs). Finally, applications of BCI navigation to scenarios outside the laboratory; research challenges, including human factors in navigation application interaction design; and the feasibility of hybrid BCI for BCI navigation are discussed in detail.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579622000134/pdf?md5=5a4f8528dc3cdff184c54e71eee21d0b&pid=1-s2.0-S2096579622000134-main.pdf","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Virtual Reality Intelligent Hardware","FirstCategoryId":"1093","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096579622000134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 4

Abstract

A brain-computer interface (BCI) facilitates bypassing the peripheral nervous system and directly communicating with surrounding devices. Navigation technology using BCI has developed—from exploring the prototype paradigm in the virtual environment (VE) to accurately completing the locomotion intention of the operator in the form of a powered wheelchair or mobile robot in a real environment. This paper summarizes BCI navigation applications that have been used in both real and VEs in the past 20 years. Horizontal comparisons were conducted between various paradigms applied to BCI and their unique signal-processing methods. Owing to the shift in the control mode from synchronous to asynchronous, the development trend of navigation applications in the VE was also reviewed. The contrast between highlevel commands and low-level commands is introduced as the main line to review the two major applications of BCI navigation in real environments: mobile robots and unmanned aerial vehicles (UAVs). Finally, applications of BCI navigation to scenarios outside the laboratory; research challenges, including human factors in navigation application interaction design; and the feasibility of hybrid BCI for BCI navigation are discussed in detail.

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
使用脑机接口在虚拟和真实环境中导航的进展报告
脑机接口(BCI)有助于绕过外周神经系统,直接与周围设备通信。使用脑机接口的导航技术已经发展起来——从在虚拟环境(VE)中探索原型范式,到在真实环境中以电动轮椅或移动机器人的形式准确完成操作员的移动意图。本文总结了近20年来在真实和虚拟现实中使用的脑机接口导航应用。对应用于脑机接口的各种范式及其独特的信号处理方法进行了横向比较。由于控制模式从同步向异步的转变,还回顾了VE中导航应用的发展趋势。以高级命令和低级命令的对比为主线,回顾了脑机接口导航在现实环境中的两大应用:移动机器人和无人机。最后,脑机接口导航在实验室外场景中的应用;研究挑战,包括导航应用交互设计中的人为因素;并详细讨论了混合脑机接口在脑机接口导航中的可行性。
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
Virtual Reality  Intelligent Hardware
Virtual Reality Intelligent Hardware Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
6.40
自引率
0.00%
发文量
35
审稿时长
12 weeks
期刊最新文献
S2ANet: Combining local spectral and spatial point grouping for point cloud processing MKEAH: Multimodal knowledge extraction and accumulation based on hyperplane embedding for knowledge-based visual question answering Generating animatable 3D cartoon faces from single portraits Robust blind image watermarking based on interest points Multi-scale context-aware network for continuous sign language recognition
×
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