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Brain-Switches for Asynchronous Brain-Computer Interfaces: A Systematic Review

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dc.contributor.authorHan, Chang-Hee-
dc.contributor.authorMueller, Klaus-Robert-
dc.contributor.authorHwang, Han-Jeong-
dc.date.accessioned2021-08-31T08:48:23Z-
dc.date.available2021-08-31T08:48:23Z-
dc.date.created2021-06-18-
dc.date.issued2020-03-
dc.identifier.issn2079-9292-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/57478-
dc.description.abstractA brain-computer interface (BCI) has been extensively studied to develop a novel communication system for disabled people using their brain activities. An asynchronous BCI system is more realistic and practical than a synchronous BCI system, in that, BCI commands can be generated whenever the user wants. However, the relatively low performance of an asynchronous BCI system is problematic because redundant BCI commands are required to correct false-positive operations. To significantly reduce the number of false-positive operations of an asynchronous BCI system, a two-step approach has been proposed using a brain-switch that first determines whether the user wants to use an asynchronous BCI system before the operation of the asynchronous BCI system. This study presents a systematic review of the state-of-the-art brain-switch techniques and future research directions. To this end, we reviewed brain-switch research articles published from 2000 to 2019 in terms of their (a) neuroimaging modality, (b) paradigm, (c) operation algorithm, and (d) performance.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherMDPI-
dc.subjectSELF-PACED OPERATION-
dc.subjectMOTOR IMAGERY-
dc.subjectNEURAL-NETWORKS-
dc.subjectINITIAL DIPS-
dc.subjectBCI SYSTEM-
dc.subjectEEG-
dc.subjectSSVEP-
dc.subjectWHEELCHAIR-
dc.subjectNIRS-
dc.subjectCLASSIFICATION-
dc.titleBrain-Switches for Asynchronous Brain-Computer Interfaces: A Systematic Review-
dc.typeArticle-
dc.contributor.affiliatedAuthorMueller, Klaus-Robert-
dc.contributor.affiliatedAuthorHwang, Han-Jeong-
dc.identifier.doi10.3390/electronics9030422-
dc.identifier.scopusid2-s2.0-85083838872-
dc.identifier.wosid000524079100043-
dc.identifier.bibliographicCitationELECTRONICS, v.9, no.3-
dc.relation.isPartOfELECTRONICS-
dc.citation.titleELECTRONICS-
dc.citation.volume9-
dc.citation.number3-
dc.type.rimsART-
dc.type.docTypeReview-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.subject.keywordPlusSELF-PACED OPERATION-
dc.subject.keywordPlusMOTOR IMAGERY-
dc.subject.keywordPlusNEURAL-NETWORKS-
dc.subject.keywordPlusINITIAL DIPS-
dc.subject.keywordPlusBCI SYSTEM-
dc.subject.keywordPlusEEG-
dc.subject.keywordPlusSSVEP-
dc.subject.keywordPlusWHEELCHAIR-
dc.subject.keywordPlusNIRS-
dc.subject.keywordPlusCLASSIFICATION-
dc.subject.keywordAuthorbrain-switch-
dc.subject.keywordAuthorbrain-computer interface-
dc.subject.keywordAuthorelectroencephalography-
dc.subject.keywordAuthornear-infrared spectroscopy-
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