ビット形式の情報提示方法によるNIRSを用いた文字入力支援システムに関する検討

カテゴリ: 論文誌(論文単位)

グループ名: 【E】センサ・マイクロマシン部門

発行日: 2012/10/01

タイトル(英語): A Study on Assisting System for Inputting Character using NIRS by the Stimulus Presentation Method of Bit Form

著者名: 後藤　かをり（富山大学大学院理工学研究部（工学）），参沢　匡将（富山大学大学院理工学研究部（工学）），下川　哲矢（東京理科大学経営学部），広林　茂樹（富山大学大学院理工学研究部（工学））

著者名(英語): Kaori Goto (Graduate School of Science and Engineering, University of Toyama), Tadanobu Misawa (Graduate School of Science and Engineering, University of Toyama), Tetsuya Shimokawa (The School of Management, Tokyo University of Science), Shigeki Hirobayashi (Graduate School of Science and Engineering, University of Toyama)

キーワード: 近赤外分光法，ブレイン・コンピュータ・インターフェース，前頭前野，暗算，単一試行分類　　Near Infrared Spectroscopy (NIRS)，Brain-Computer Interface (BCI)，prefrontal cortex，mental arithmetic，single-trial classification

要約(英語): Recent developments in non-invasive neuroimaging technologies have allowed for research on a brain-computer interface (BCI). A BCI is a system that operates a machine using only brain activity. Thus, a BCI is expected to help people with disabilities, assisting them in communicating or making decisions. In this study, we focused on assisting with spelling. Therefore, our purpose in conducting this study was to develop a BCI system for assisting with spelling. To develop our system, we used near-infrared spectroscopy (NIRS) to measure brain activity in the prefrontal cortex region. Mental arithmetic was the method of stimulating the activity of the brain. As a result of the experiment, the individual variation was observed in each participant, in the channel and timing of activating the brain. Therefore, the method by which the system automatically selects learning and classification data was introduced. In addition, we proposed the stimulus presentation method of “bit form” to replace the “matrix form” used commonly by previous researches. Then the classification accuracy was verified offline. As a result of this analysis, classification accuracy enhancement to 78.47% has been shown by support vector machine (SVM). Though additional examination is needed, the future potential of this system using NIRS was demonstrated.

本誌: 電気学会論文誌E（センサ・マイクロマシン部門誌） Vol.132 No.10 （2012） 特集：脳機能計測技術

本誌掲載ページ: 328-336 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejsmas/132/10/132_328/_article/-char/ja/