独立成分分析を用いた脳磁界計測のノイズ軽減に関する研究 A study on noise reduction using ICA for Magnetoencephalography

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In the biomagnetic measurement, the biomagnetic signal is extremely weak compared with environmental magnetic noise. Therefore, it is important to reduce the noise component. There are many noise-reduction studies for MEG using Independent Component Analysis (ICA). The ICA method is expectable to extract and remove noise components from the brain magnetic field measurement data. However, in these researches, each obtained independent components are artificially distinguished to the noise and the signal. We propose a method of distinguishing to the noise and the signal automatically by using the signal subspace method for vector brain magnetic field. By applying this method to a phantom data and Auditory Evoked Field data, it is shown improvement of the signal to noise ratio and estimated accuracy.

収録刊行物

  • 電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society

    電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society 124(9), 1685-1691, 2004-09-01

    The Institute of Electrical Engineers of Japan

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各種コード

  • NII論文ID(NAID)
    10013538458
  • NII書誌ID(NCID)
    AN10065950
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    03854221
  • NDL 記事登録ID
    7076666
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-795
  • データ提供元
    CJP書誌  NDL  J-STAGE 
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