2019 Fiscal Year Final Research Report
Development the brain-machine interface with optimal recognition of environmental information and users' intention
| Project/Area Number |
17K19998
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| Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Human informatics and related fields
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Kiyoshi Kotani 東京大学, 先端科学技術研究センター, 准教授 (00372409)
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| Project Period (FY) |
2017-06-30 – 2020-03-31
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| Keywords | Brain-Machine interface / P300 |
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| Outline of Final Research Achievements |
In order to construct a Brain-Computer Interface that has a high affinity with environmental information, we have developed a wheelchair driving system for Mixed Reality.
After a basic study of the optical see-through system, we built a system that actually drives a wheelchair based on the users' intentions by combining a stimulus presentation method, EEG signal processing, and EEG discrimination into a single system and then operating it in real time. The accuracy of the successful movement to a given location was 68%.
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| Free Research Field |
生体信号処理
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では，基礎的な刺激や識別手法の検討を行った後に，実際に利用者意図に基づいて車いすを駆動するシステムを構築したという点で社会的な意義を果たした研究と考えられる．環境情報を考慮したスマートかつ利用者にとって自然な情報提示に基づく車いす駆動システムを構築することができた．利用者は仮想マーカが配置された場所であればどこにでも移動することができ，従来の運動想起型BMIによる車いす操作に比べると，特別な訓練が不要であることや移動方向を常にイメージしなくても一度の指令で移動可能などの利点を持つ．
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