Development of Semi-Autonomous Device Control System for Brain Machine Interface
| Project/Area Number |
25702035
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| Research Category |
Grant-in-Aid for Young Scientists (A)
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| Allocation Type | Partial Multi-year Fund |
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| Research Field |
Rehabilitation science/Welfare engineering
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| Research Institution | Gifu University (2014-2016)
Osaka University (2013) |
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Principal Investigator |
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| Project Period (FY) |
2013-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥19,240,000 (Direct Cost: ¥14,800,000、Indirect Cost: ¥4,440,000)
Fiscal Year 2016: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2015: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2014: ¥7,150,000 (Direct Cost: ¥5,500,000、Indirect Cost: ¥1,650,000)
Fiscal Year 2013: ¥7,670,000 (Direct Cost: ¥5,900,000、Indirect Cost: ¥1,770,000)
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| Keywords | 福祉ロボティクス / ブレイン・マシン・インターフェース / 生体信号解析 / ブレインマシンインターフェース / 福祉ロボット / 運動解析 / ブレイン・マシン・インターフェス / 体内埋込装置 / 姿勢推定 / 福祉機器 |
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| Outline of Final Research Achievements |
Recent brain machine interface (BMI) technology achieved real-time robot arm control based on the brain wave “ECoG (Electro-Corti-Gram)”: (1) To measure ECoG with the electrodes on the human cortex; (2) to discriminate movements from ECoG with machine learning; (3) to operate a robot arm based on the discrimination results. Thus, BMI application is expected for medical use and it becomes an urgent and important issue to improve the discrimination rate. Therefore in this research, autonomous control algorithm is proposed for compensating such discrimination errors. Then, the performance of the proposed system is investigated with not only brain wave but also other major bio-signals for welfare device control.
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Report
(5 results)
Research Products
(7 results)
