Presentation 2010-07-09
The estimation of brain function change using neural network
Makoto FUJIWARA, Masatake AKUTAGAWA, Yousuke KINOUCHI, Hirohumi NAGASHINO, Takahiro EMOTO,
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Abstract(in English) As means to know the function of the brain, technique to observe brain waves (EEG) is used mainly by the cheap sheath convenience, the fewness of the accident. However, it becomes important to monitor whether the state of the brain changed because the correspondence that accepted the change of the condition of the patient is demanded in the case of the clinical spot operated on. When a frequency band is unclear, there is it in the case of such situation, and the method to detect the change that is in a state of the brain is demanded without foreknowledge. Therefore I apply the technique to analyze an expensive signal with NN of the nonlinearity to analysis in EEG in this study and examine the index of the state change of the brain.
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Keyword(in English) EEG / neural network / Randomness
Paper # MBE2010-18
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Conference Information
Committee MBE
Conference Date 2010/7/2(1days)
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Paper Information
Registration To ME and Bio Cybernetics (MBE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) The estimation of brain function change using neural network
Sub Title (in English)
Keyword(1) EEG
Keyword(2) neural network
Keyword(3) Randomness
1st Author's Name Makoto FUJIWARA
1st Author's Affiliation Graduate School of Advanced Technology, The University of Tokushima Graduate School()
2nd Author's Name Masatake AKUTAGAWA
2nd Author's Affiliation Institute of Technology and Science, The University of Tokushima Graduate School
3rd Author's Name Yousuke KINOUCHI
3rd Author's Affiliation Institute of Technology and Science, The University of Tokushima Graduate School
4th Author's Name Hirohumi NAGASHINO
4th Author's Affiliation Institute of Health Biosciences, The University of Tokushima Graduate school
5th Author's Name Takahiro EMOTO
5th Author's Affiliation Institute of Technology and Science, The University of Tokushima Graduate School
Date 2010-07-09
Paper # MBE2010-18
Volume (vol) vol.110
Number (no) 120
Page pp.pp.-
#Pages 4
Date of Issue