Article(id=1242139468338115238, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242139451439259857, articleNumber=null, orderNo=14, doi=10.3981/j.issn.1000-7857.2021.19.007, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1591545600000, receivedDateStr=2020-06-08, revisedDate=1592841600000, revisedDateStr=2020-06-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1636362401123, onlineDateStr=2021-11-08, pubDate=1634054400000, pubDateStr=2021-10-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1636362401123, onlineIssueDateStr=2021-11-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774078727083, creator=sys-migrate, updateTime=1774078727083, updator=sys-migrate, issue=Issue{id=1242139451439259857, tenantId=1146029695717560320, journalId=1146031591421210625, year='2021', volume='39', issue='19', pageStart='0', pageEnd='108', issueExtLink='null', onlineDate='null', pubDate='1634054400000', pubDateStr='2021-10-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774078723055, creator='sys-migrate', updateTime=1774078723055, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=56, endPage=65, ext={EN=ArticleExt(id=1242139473698435788, articleId=1242139468338115238, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Hot topics review of brain-computer interface in 2019-2020, columnId=1242116810380743325, journalTitle=Science & Technology Review, columnName=Reviews, runingTitle=null, highlight=null, articleAbstract=Brain-computer interface (BCI) is designed to provide rich and powerful command signals for assistive devices by decoding user's intention directly from brain signals in a real-time way. Recently, both theoretic and practical aspects of BCI technology have rapidly developed and become increasingly mature. More application scenarios of BCI technology have been demonstrated as well. This review summarizes the important achievements and events in hardware, algorithm, paradigm, and application in the BCI field in 2019-2020 and discusses its development trend., authors=CHEN Xiaogang¹, YANG Chen², CHEN Jingjing³, GAO Xiaorong³, authorsList=CHEN Xiaogang, YANG Chen, CHEN Jingjing, GAO Xiaorong, authorCompany=1. Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300192, China;
2. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
3. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=2NPqltT+0JVHhqUSLa+Tpw==, pdfFileSize=4304573, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242139470988910856, articleId=1242139468338115238, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=脑机接口技术发展新趋势——基于2019—2020年研究进展, columnId=1242134377686180284, journalTitle=科技导报, columnName=综述, runingTitle=null, highlight=null, articleAbstract=脑机接口旨在通过直接从大脑信号中实时解码用户意图来为辅助设备提供丰富、强大的命令信号。近年来，脑机接口技术的理论和实际应用的研究进展迅速，技术日趋成熟，其应用领域也在不断扩大。概述了2019—2020年脑机接口领域在硬件、算法、范式、应用等方面取得的重要研究进展和发生的热点事件，展望了未来脑机接口技术的发展趋势。, authors=陈小刚¹, 杨晨², 陈菁菁³, 高小榕³, authorsList=陈小刚, 杨晨, 陈菁菁, 高小榕, authorCompany=1. 中国医学科学院北京协和医学院生物医学工程研究所, 天津 300192;
2. 北京邮电大学电子工程学院, 北京 100876;
3. 清华大学医学院生物医学工程系, 北京 100084, correspAuthors=null, authorNote=陈小刚,副研究员,研究方向为脑机接口,电子信箱:chenxg@bme.cams.cn, correspAuthorsNote=高小榕(通信作者),教授,研究方向为脑机接口,电子信箱:gxr-dea@tsinghua.edu.cn, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=T3irRtQ7eBep/bowuSYC9A==, pdfFileSize=4304573, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=国家重点研发计划项目（2017YFB1002505）；广东省重点领域研发计划项目（2018B030339001）；中央高校基本科研业务费专项资金项目（3332019015，3332018191）)}, authors=null, keywords=[Keyword(id=1242139470682731182, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242139468338115238, language=CN, orderNo=1, keyword=脑机接口), Keyword(id=1242139470770811568, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242139468338115238, 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