| Project/Area Number |
18K18023
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 60040:Computer system-related
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| Research Institution | Osaka University (2019)
University of Yamanashi (2018) |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 脳波 / 圧縮センシング / 独立成分分析 / 脳波計測 |
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| Outline of Final Research Achievements |
A novel compressed sensing (CS) framework for electroencephalogram (EEG) signals with artifacts was proposed in this research. A feature of this framework is the application of an independent component analysis (ICA) to remove the interference of artifacts after compression in a data processing unit. Therefore, we can remove the power-hungry ICA processing block from the sensing unit. The proposed framework is evaluated using raw EEG signals with a pseudo-model of an eye-blinking artifact.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では，圧縮センシングと独立成分分析を用いた新しい脳波計測フレームワークに関する研究を実施した．圧縮センシングを計測システムに応用する際に生じる課題に対して，センシングユニットにおける回路ブロックの追加を避けつつ解決出来る方法を学会で提案する等，学術的に意義のある成果を発信した．本研究成果は，圧縮センシングを実社会で利用する上での一つの解決策を示すことが出来たという点で社会的意義があるといえる．
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