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김성필

Kim, Sung-Phil
Brain-Computer Interface Lab.
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dc.citation.startPage 783203 -
dc.citation.title BIOMED RESEARCH INTERNATIONAL -
dc.citation.volume 2014 -
dc.contributor.author Ryun, Seokyun -
dc.contributor.author Kim, June Sic -
dc.contributor.author Lee, Sang Hun -
dc.contributor.author Jeong, Sehyoon -
dc.contributor.author Kim, Sung-Phil -
dc.contributor.author Chung, Chun Kee -
dc.date.accessioned 2023-12-22T02:36:45Z -
dc.date.available 2023-12-22T02:36:45Z -
dc.date.created 2014-09-18 -
dc.date.issued 2014-07 -
dc.description.abstract Power changes in specific frequency bands are typical brain responses during motor planning or preparation. Many studies have demonstrated that, in addition to the premotor, supplementary motor, and primary sensorimotor areas, the prefrontal area contributes to generating such responses. However, most brain-computer interface (BCI) studies have focused on the primary sensorimotor area and have estimated movements using postonset period brain signals. Our aim was to determine whether the prefrontal area could contribute to the prediction of voluntary movement types before movement onset. In our study, electrocorticography (ECoG) was recorded from six epilepsy patients while performing two self-paced tasks: hand grasping and elbow flexion. The prefrontal area was sufficient to allow classification of different movements through the area's premovement signals (-2.0 s to 0 s) in four subjects. The most pronounced power difference frequency band was the beta band (13-30Hz). The movement prediction rate during single trial estimation averaged 74% across the six subjects. Our results suggest that premovement signals in the prefrontal area are useful in distinguishing different movement tasks and that the beta band is the most informative for prediction of movement type before movement onset. -
dc.identifier.bibliographicCitation BIOMED RESEARCH INTERNATIONAL, v.2014, pp.783203 -
dc.identifier.doi 10.1155/2014/783203 -
dc.identifier.issn 2314-6133 -
dc.identifier.scopusid 2-s2.0-84929051850 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/6224 -
dc.identifier.wosid 000339753200001 -
dc.language 영어 -
dc.publisher HINDAWI PUBLISHING CORPORATION -
dc.title Movement Type Prediction before Its Onset Using Signals from Prefrontal Area: An Electrocorticography Study -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Biotechnology & Applied Microbiology; Medicine, Research & Experimental -
dc.relation.journalResearchArea Biotechnology & Applied Microbiology; Research & Experimental Medicine -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -

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