カテゴリ: 論文誌(論文単位)グループ名: 【C】電子・情報・システム部門発行日: 2024/11/01タイトル(英語): EEG Analysis during Recall of Computational Load Task著者名: 布本 優太（立命館大学 理工学研究科），馬杉 正男（立命館大学 理工学研究科）著者名(英語): Yuta Nunomoto (Ritsumeikan University), Masao Masugi (Ritsumeikan University)キーワード: 脳波，脈波，自律神経，サポートベクターマシン EEG，pulse wave，autonomic nerves，SVM要約(英語): This paper describes an analysis of EEG signals during the recall of computational load task (or mental arithmetic). For this purpose, feature values were extracted from measured data from multiple EEG electrodes (F3, F4, FC3, etc.) under two conditions: resting state and mental arithmetic image recall state. When we applied SVM (Support-Vector Machine) using features obtained from brain wave component ratios of 20 subjects, the classification accuracy was 72.8%. Subsequently, to correct the classification accuracy, we focused on the heart rate, which reflects the balance of the autonomic nervous system. As a result, when excluding individuals with relatively fast heart rates from the dataset based on their resting state, the classification accuracy improved with results up to 90.2%. Furthermore, when excluding individuals with relatively slow heart rates from the dataset, the classification accuracy decreased to less than 60%.本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.144 No.11 （2024） 特集Ⅰ：電気関係学会関西連合大会 特集Ⅱ：電子材料関連技術の最近の進展本誌掲載ページ: 1124-1125 p原稿種別: 研究開発レター／日本語電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/144/11/144_1124/_article/-char/ja/
