| Project/Area Number |
12450166
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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 |
Measurement engineering
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| Research Institution | Kyushu Institute of Technology |
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Principal Investigator |
INOUE Katsuhiro Kyushu Institute of Technology, Faculty of computer Science and Systems Engineering, Department of Control Engineering and Science, Associate Professor, 情報工学部, 助教授 (00150516)
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| Co-Investigator(Kenkyū-buntansha) |
MAEDA Makoto Kyushu Institute of Technology, Faculty of computer Science and Systems Engineering, Department of Control Engineering and Science, Research Associate, 情報工学部, 助手 (00274556)
KUMAMARU Kousuke Kyushu Institute of Technology, Faculty of computer Science and Systems Engineering, Department of Control Engineering and Science, Professor, 情報工学部, 教授 (30037949)
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| Project Period (FY) |
2000 – 2003
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| Project Status |
Completed (Fiscal Year 2003)
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| Budget Amount *help |
¥14,700,000 (Direct Cost: ¥14,700,000)
Fiscal Year 2003: ¥2,000,000 (Direct Cost: ¥2,000,000)
Fiscal Year 2002: ¥2,500,000 (Direct Cost: ¥2,500,000)
Fiscal Year 2001: ¥1,900,000 (Direct Cost: ¥1,900,000)
Fiscal Year 2000: ¥8,300,000 (Direct Cost: ¥8,300,000)
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| Keywords | Electroencephalogram / Event Related Potential / Evoked Response / Identification / Pattern Recognition / Signal Processing / AR Model / Man-machine Interface / 選択反応実験 / 確率システム / 確立システム |
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| Research Abstract |
In this research project, the identification methods of electroencephalogram (EEG) signals related to the movement and recognition were studied in order to identify human's will from the EEG, and to apply to the man-machine interface. And the following results were obtained.
1.Change detection of EEG wave related to movement
Some kinds of method (Direct information analysis, Statistical pattern recognition based on AR model or Quasi-AR model etc.) were tried to analyze the EEG waves (2ch:C3, C4) recorded during right and left hand imagery. And the following facts were confirmed. The EEG wave can be discriminated with the accuracy of 85% or more for the subjects who learned enough. The information flow between C3 and C4 has bias according to the imagined hand (right or left). The discrimination accuracy can be improved by using the clustering technique together or applying the Quasi-AR model when high accuracy is not obtained by the usual method. The subjects can adapt up to a point of the system composed of parameters based on other subject.
2.Identification of EEG wave under the visual stimulus or auditory stimulus
The response EEG wave related to the visual stimulus and the auditory stimulus was analyzed in order to detect the malfunction in contradiction to subjects will from the EEG wave in the man-machine interface. And it was confirmed that there may be some features in frequency shift, and in a temporal response of the electrode position with high EEG amplitude.
3.Application to man-machine interface
The system that operated AIBO (made by SONY) based on information from the EEG wave was made, and the optimal parameter such as processing data lengths and operation instruction intervals was examined. The experiments to healthy persons are performed, and the problem on practical use was examined.
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