DSpace at KISTKIST Conference Paper2018

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dc.contributor.authorChoi, Junhyuk-
dc.contributor.authorLee, Song Joo-
dc.contributor.authorKim, Seung Jong-
dc.contributor.authorLee, Jong Min-
dc.contributor.authorKim, Hyungmin-
dc.date.accessioned2024-01-19T10:39:32Z-
dc.date.available2024-01-19T10:39:32Z-
dc.date.created2022-02-28-
dc.date.issued2018-01-16-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/114379-
dc.description.abstractIn this study, we employed a linear classifier to grasp the abstract features of electroencephalography (EEG) for recognizing voluntary gait intention and termination. We monitored Mu-band EEG to find gait intention and tried to detect a movement on/offset. Considerable gait-related (de) synchronization occurred hence, amplified by common spatial pattern (CSP). Performance of the classifier was evaluated in terms of classification success rates and false positive rates.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleDetecting Voluntary Gait Initiation/Termination Intention Using EEG-
dc.typeConference-
dc.identifier.doi10.1109/IWW-BCI.2018.8311532-
dc.description.journalClass1-
dc.identifier.bibliographicCitation6th International Winter Conference on Brain-Computer Interface (BCI), pp.185 - 187-
dc.citation.title6th International Winter Conference on Brain-Computer Interface (BCI)-
dc.citation.startPage185-
dc.citation.endPage187-
dc.citation.conferencePlaceKO-
dc.citation.conferencePlace하이원리조트 Korea-
dc.citation.conferenceDate2018-01-15-
dc.relation.isPartOf2018 6TH INTERNATIONAL CONFERENCE ON BRAIN-COMPUTER INTERFACE (BCI)-
dc.identifier.wosid000458446600047-
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KIST Conference Paper > 2018
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