| Project/Area Number |
20300196
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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 |
Rehabilitation science/Welfare engineering
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| Research Institution | Kyushu Institute of Technology |
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Principal Investigator |
YAMAZAKI Toshimasa Kyushu Institute of Technology, 大学院・情報工学研究院, 教授 (50392163)
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| Co-Investigator(Kenkyū-buntansha) |
INOUE Katsuhiro 九州工業大学, 大学院・情報工学研究院, 教授 (00150516)
MAEDA Makoto 九州工業大学, 大学院・情報工学研究院, 助教 (00274556)
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| Project Period (FY) |
2008 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥14,950,000 (Direct Cost: ¥11,500,000、Indirect Cost: ¥3,450,000)
Fiscal Year 2010: ¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2009: ¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2008: ¥6,240,000 (Direct Cost: ¥4,800,000、Indirect Cost: ¥1,440,000)
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| Keywords | ヒューマンインターフェース / 単一試行脳波 / BCI / ICA / ECDL / 数量化分析II類 / LOOCV / DBN / Bereitschaftpotential / 確率推論 / 標準脳 |
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| Research Abstract |
A new single-trial-EEG-based Brain-Computer Interface (BCI) was developed using independent component analysis (ICA), equivalent current dipole source localization (ECDL) and dynamic Bayesian Network (DBN). Quantification Method of type II (QM2) and the BN were used as learning model for categorical data. All the QM2 models for the seven subjects had correlation ratios of more than 0.9, yielding the good discrimination between left and right hands to be imagined, and the correction rates in LOOCV of more than 0.8. Using the obtained BN, the classification rule was established on the basis of the conditional probabilities in the "motor cortex" nodes. Moreover, the generalization to the DBN allowed us to apply to the Bereitschaftpotential, and led to the better performance of the classification rule.
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