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논문KCI 등재

뉴로피드백 효과에 따른 EEG 기반 BCI 동작 상상 성능 평가 요소별 정확도 비교

Accuracy Comparison of Motor Imagery Performance Evaluation Factors Using EEG Based Brain Computer Interface by Neurofeedback Effectiveness

류연수|민세동|이명호|이영범|최동학
대한의용생체공학회 (The Korea Society Of Medical & Biological Engineering)|2011.12|의공학회지 (Journal of biomedical Engineering Research)|제32권 제4호|pp. 295-304

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키워드

neurofeedbackclassifierchannelwindow sizeelectroencephalography (EEG)brain computer interface (BCI)motor imagerycommon spatial pattern (CSP)EEG modefeature vector calculation

초록

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.

Abstract

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.

참고문헌 (56)

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