Presentation 2014-09-12
Proposal of Digitization of Electroencephalogram by Using Hilbert-Huang Transform and Its Application to Biometrics
Ryota HORIE, Noriki ITO,
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Abstract(in English) We proposed a new method to extract features from non-stationary EEG signals with long time context, like EEG during listening music. In the method, an EEG signal was decomposed into narrowband signals, called intrinsic mode function. Polarity of the function was obtained based on the function's spontaneous phase and encoded into 2 symbols. Entropy, which indicates biased appearance of a symbol, was calculated on every sample points. An experimental result showed biased appearances of a symbol in particular timing of the music in particular narrowband signals in particular channels. If the biased appearances of a symbol is stably appeared in a person and differently appeared in other persons, the symbol sequence can be applied as a feature for personal identification.
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Keyword(in English) Hilbert-Huang Transform / Electroencephalogram / Digitization / Biometrics
Paper # BioX2014-14,MBE2014-37
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Committee MBE
Conference Date 2014/9/5(1days)
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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) Proposal of Digitization of Electroencephalogram by Using Hilbert-Huang Transform and Its Application to Biometrics
Sub Title (in English)
Keyword(1) Hilbert-Huang Transform
Keyword(2) Electroencephalogram
Keyword(3) Digitization
Keyword(4) Biometrics
1st Author's Name Ryota HORIE
1st Author's Affiliation College of Engineering, Shibaura Institute of Technology()
2nd Author's Name Noriki ITO
2nd Author's Affiliation College of Engineering, Shibaura Institute of Technology
Date 2014-09-12
Paper # BioX2014-14,MBE2014-37
Volume (vol) vol.114
Number (no) 213
Page pp.pp.-
#Pages 4
Date of Issue