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KMID : 1137820110320040295
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의공학회지
2011 Volume.32 No. 4 p.295 ~ p.304
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Accuracy Comparison of Motor Imagery Performance Evaluation Factors Using EEG Based Brain Computer Interface by Neurofeedback Effectiveness
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Choi Donghag
Ryu Yonsu
Lee Young-Bum
Min Se-Dong
Lee Myoung-Ho
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Abstract
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In this study, we evaluated the EEG based BCI algorithm using common spatial pattern to find realistic applicability using neurofeedback EEG based BCI algorithm - EEG mode, feature vector calculation, the number of selected channels, 3 types of classifier, window size is evaluated for 10 subjects. The experimental results have been evaluated depending on conditioned experiment whether neurofeedback is used or not In case of using neurofeedback, a few subjects presented exceptional but general tendency presented the performance improvement Through this study, we found a motivation of development for the specific classifier based BCI system and the assessment evaluation system. We proposed a need for an optimized algorithm applicable to the robust motor imagery evaluation system with more useful functionalities.
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KEYWORD
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electroencephalography (EEG), brain computer interface (BCI), motor imagery, neurofeedback, common spatial pattern (CSP), EEG mode, feature vector calculation, channel, classifier, window size
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