Improving Motor Imagery-BCI Performance with Weighted Trial Neurofeedback

カテゴリ: 部門大会

論文No: SS2-5

グループ名: 【C】2022年電気学会電子・情報・システム部門大会

発行日: 2022/08/24

タイトル(英語): Improving Motor Imagery-BCI Performance with Weighted Trial Neurofeedback

著者名: Connelly Akima（東京工業大学）,Rangpong Phurin（東京工業大学）,Li Pengcheng（東京工業大学）,Wilaiprasitporn Theerawit（Vidyasirimedhi Institute of Science and Technology）,Yagi Tohru（東京工業大学）

著者名(英語): Akima Connelly (Tokyo Institute Technology),Phurin Rangpong (Tokyo Institute Technology),Pengcheng Li (Tokyo Institute Technology),Theerawit Wilaiprasitporn (Vidyasirimedhi Institute of Science and Technology),Tohru Yagi (Tokyo Institute Technology)

キーワード: Electroencephalography (EEG)|Brain-Computer Interface (BCI)|Motor Imagery (MI)|Neurofeedback|BCI illiteracy|Electroencephalography (EEG)|Brain-Computer Interface (BCI)|Motor Imagery (MI)|Neurofeedback|BCI illiteracy

要約(日本語): Motor-imagery (MI) classification based on electroencephalography (EEG) has been extensively studied and recently used more in brain-computer interfaces (BCI). MI-BCI is a system that utilizes recorded brain activity to communicate between the brain and computer. A common obstacle for MI-BCI is the inability of some participants to perform the BCI task, called BCI illiteracy. Various training protocols are investigated to improve the systems use the brain activity from MI tasks which are the imagination of motor actions without performing them. Our research aims to improve participants' performance in MI-BCI by weighting the conditions in neurofeedback to the poor performing task.