Integrated control system using bidirectional learning between neural system and machine
| Project/Area Number |
17300142
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Biomedical engineering/Biological material science
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| Research Institution | The University of Tokyo |
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Principal Investigator |
SUZUKI Takafumi The University of Tokyo, Graduate School of Information Science and Technology, Specially Appointed Lecturer, 大学院情報理工学系研究科, 研究拠点形成特任教員 (50302659)
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| Co-Investigator(Kenkyū-buntansha) |
MABUCHI Kunihiko The University of Tokyo, Graduate School of Information Science and Technology, Professor, 大学院情報理工学系研究科, 教授 (50192349)
TAKEUCHI Shoji The University of Tokyo, Institute of Industrial Science, Associate Professor, 生産技術研究所, 助教授 (90343110)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥14,900,000 (Direct Cost: ¥14,900,000)
Fiscal Year 2006: ¥5,000,000 (Direct Cost: ¥5,000,000)
Fiscal Year 2005: ¥9,900,000 (Direct Cost: ¥9,900,000)
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| Keywords | Neural Interface / Brain-Machine Interface / Nerve Electrode / Brain / Nerve / Plasticity / ブレインマシンインターフェース |
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| Research Abstract |
The goal of this project is to develop an integrated control system using bidirectional learning between neural system and an artificial machine, in order to attain a brain-machine interface (BMI) system which has higher control performance.
Recently many research groups around the world have been focusing on BMI systems in which for examples artificial limb system or a wheelchair can be controlled with motor information derived from patients in the same way as patients control their own limbs. Neural systems have such an flexible plasticity capability that once they are connected to a BMI system they easily change their input-output characteristics. So we have focused on this brain flexibility to achieve high performance BMI systems.
The research tasks we have conducted were
1. Development of a recording system capable of stable measurement of neural signals chronically.
2. Design and fabrication of a neural control system in which a vehicle system was controlled by neural information recorded from the motor cortex of rats
3. Measurement and analysis of the plasticity of rat's brain during the chronic experiments in which variable control conditions including the feedback method and the control algorithm were applied.
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Report
(3 results)
Research Products
(35 results)
