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Developments in brain-machine interfaces from the perspective of robotics

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dc.contributor.authorKim, Hyun K.-
dc.contributor.authorPark, Shinsuk-
dc.contributor.authorSrinivasan, Mandayam A.-
dc.date.accessioned2021-09-08T18:34:46Z-
dc.date.available2021-09-08T18:34:46Z-
dc.date.created2021-06-10-
dc.date.issued2009-04-
dc.identifier.issn0167-9457-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/120363-
dc.description.abstractMany patients suffer from the loss of motor skills, resulting from traumatic brain and spinal cord injuries, stroke, and many other disabling conditions. Thanks to technological advances in measuring and decoding the electrical activity of cortical neurons, brain-machine interfaces (BMI) have become a promising technology that can aid paralyzed individuals. In recent studies on BMI, robotic manipulators have demonstrated their potential as neuroprostheses. Restoring motor skills through robot manipulators controlled by brain signals may improve the quality of life of people with disability. This article reviews current robotic technologies that are relevant to BMI and suggests strategies that could improve the effectiveness of a brain-operated neuroprosthesis through robotics. (C) 2009 Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER-
dc.subjectMOTOR CORTICAL REPRESENTATION-
dc.subjectARM MOVEMENTS-
dc.subjectCOMPUTER INTERFACE-
dc.subjectMUSCLE ACTIVATION-
dc.subjectIMPEDANCE CONTROL-
dc.subjectCONTROL SIGNALS-
dc.subjectNEURAL-CONTROL-
dc.subjectFORCE-
dc.subjectCORTEX-
dc.subjectPERFORMANCE-
dc.titleDevelopments in brain-machine interfaces from the perspective of robotics-
dc.typeArticle-
dc.contributor.affiliatedAuthorPark, Shinsuk-
dc.identifier.doi10.1016/j.humov.2008.12.001-
dc.identifier.scopusid2-s2.0-61849132220-
dc.identifier.wosid000265176700003-
dc.identifier.bibliographicCitationHUMAN MOVEMENT SCIENCE, v.28, no.2, pp.191 - 203-
dc.relation.isPartOfHUMAN MOVEMENT SCIENCE-
dc.citation.titleHUMAN MOVEMENT SCIENCE-
dc.citation.volume28-
dc.citation.number2-
dc.citation.startPage191-
dc.citation.endPage203-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaNeurosciences & Neurology-
dc.relation.journalResearchAreaPsychology-
dc.relation.journalResearchAreaSport Sciences-
dc.relation.journalWebOfScienceCategoryNeurosciences-
dc.relation.journalWebOfScienceCategoryPsychology-
dc.relation.journalWebOfScienceCategoryPsychology, Experimental-
dc.relation.journalWebOfScienceCategorySport Sciences-
dc.subject.keywordPlusMOTOR CORTICAL REPRESENTATION-
dc.subject.keywordPlusARM MOVEMENTS-
dc.subject.keywordPlusCOMPUTER INTERFACE-
dc.subject.keywordPlusMUSCLE ACTIVATION-
dc.subject.keywordPlusIMPEDANCE CONTROL-
dc.subject.keywordPlusCONTROL SIGNALS-
dc.subject.keywordPlusNEURAL-CONTROL-
dc.subject.keywordPlusFORCE-
dc.subject.keywordPlusCORTEX-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordAuthorBrain-machine interface-
dc.subject.keywordAuthorNeuroprosthesis-
dc.subject.keywordAuthorNeuro-robot-
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