Predicting motor behavior: an efficient EEG signal processing pipeline to detect brain states with potential therapeutic relevance for VR-based neurorehabilitation

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dc.contributor.author McDermott, Eric James
dc.contributor.author Metsomaa, Johanna
dc.contributor.author Belardinelli, Paolo
dc.contributor.author Ziemann, Ulf
dc.contributor.author Zrenner, Christoph Daniel Frederik
dc.date.accessioned 2023-10-20T07:53:49Z
dc.date.available 2023-10-20T07:53:49Z
dc.date.issued 2023
dc.identifier.issn 1359-4338
dc.identifier.uri http://hdl.handle.net/10900/146623
dc.language.iso en en
dc.publisher Springer London Ltd de_DE
dc.relation.uri http://dx.doi.org/10.1007/s10055-021-00538-x
dc.subject.ddc 004 de_DE
dc.subject.ddc 610 de_DE
dc.subject.ddc 600 de_DE
dc.title Predicting motor behavior: an efficient EEG signal processing pipeline to detect brain states with potential therapeutic relevance for VR-based neurorehabilitation de_DE
dc.type Article de_DE
utue.quellen.id 20230619000000_02184
utue.publikation.seiten 347-369 de_DE
utue.personen.roh McDermott, Eric J.
utue.personen.roh Metsomaa, Johanna
utue.personen.roh Belardinelli, Paolo
utue.personen.roh Grosse-Wentrup, Moritz
utue.personen.roh Ziemann, Ulf
utue.personen.roh Zrenner, Christoph
dcterms.isPartOf.ZSTitelID Virtual Reality de_DE
dcterms.isPartOf.ZS-Issue 1 de_DE
dcterms.isPartOf.ZS-Volume 27 de_DE
utue.fakultaet 04 Medizinische Fakultät
utue.fakultaet Sonstige


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