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dc.contributor.authorHa, Jihyeon-
dc.contributor.authorKim, Laehyun-
dc.contributor.authorKim, Da-hye-
dc.date.accessioned2024-01-19T10:39:48Z-
dc.date.available2024-01-19T10:39:48Z-
dc.date.created2022-02-28-
dc.date.issued2018-01-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/114394-
dc.description.abstractThe electroencephalography (EEG) based brain-computer interface (BCI) presented a new paradigm of rehabilitation. Especially, rehabilitation incorporating EEG based BCI for stroke with motor impairment makes rehabilitation more effective than previously; for example, it provides neurofeedback to improve engagement of the brain. In this study, we measured EEG data of nine patients with chronic stroke accompanied with a unilateral motor problem while all patients performed upper limb rehabilitation (performing a grasping task with the affected hand). As a result, we found that the EEG feature showed similar EEG power spectral densities between the ipsilesional area and contralesional area. Additionally, this feature was significantly correlated (Spearman correlation coefficient rho = -0.7280, p < 0.05) with the Fugl-Meyer Assessment score of the affected hand, indicating a degree of motor function. These results showed that brain activity of patients who had low motor function bilaterally appeared in ipsilesional and contralesional areas, whereas brain activity of patients who had high motor function specifically appeared in the ipsilesional area only.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleAn approach for assessing stroke motor function ability using the similarity between electroencephalographic power spectral densities on both motor cortices-
dc.typeConference-
dc.description.journalClass1-
dc.identifier.bibliographicCitation6th International Winter Conference on Brain-Computer Interface (BCI), pp.103 - 105-
dc.citation.title6th International Winter Conference on Brain-Computer Interface (BCI)-
dc.citation.startPage103-
dc.citation.endPage105-
dc.citation.conferencePlaceUS-
dc.citation.conferencePlaceKorea Univ, Global Leader Dev Div Brain Engn, SOUTH KOREA-
dc.citation.conferenceDate2018-01-15-
dc.relation.isPartOf2018 6TH INTERNATIONAL CONFERENCE ON BRAIN-COMPUTER INTERFACE (BCI)-
dc.identifier.wosid000458446600025-
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KIST Conference Paper > 2018
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