A study on noise reduction using ICA for Magnetoencephalography
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- Kawakatsu Masaki
- School of Information Environment, Tokyo Denki Univ.
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- Ishibashi Hidenori
- School of Engineering, Tokyo Denki Univ.
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- Adachi Masaharu
- School of Engineering, Tokyo Denki Univ.
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- Uchikawa Yoshinori
- School of Science and Engineering, Tokyo Denki Univ.
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- Kotani Makoto
- School of Engineering, Tokyo Denki Univ.
Bibliographic Information
- Other Title
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- 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
- ドクリツ セイブン ブンセキ オ モチイタ ノウ ジカイ ケイソク ノ ノイズ ケイゲン ニ カンスル ケンキュウ
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Abstract
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.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 124 (9), 1685-1691, 2004
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390001204606412928
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- NII Article ID
- 10013538458
- 30011602384
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 7076666
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed