Presentation 2013-11-23
Epilepsy model and EEG analysis using the correlation between the ictal EEG channels
Shumpei WATANABE, Yasukuni MORI, Yoichi SAITO, Hajime HARADA, Ikuo MATSUBA,
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Abstract(in English) In the diagnosis of epilepsy, abnormal EEG signals are detected to grasp the condition of the patient and to decide how to treat epilepsy. Therefore, it is very important to classify EEG signals. However, the seizure of epilepsy varies widely depending on the individual patients, and the mechanism of the seizure of epilepsy is not understood yet. So detailed brain model which can classify EEG of epilepsy is needed in order to analize the mechanism. Although previous research has suggested that a macro neuron model can simulate ictal hippocampus signals, this model is not based on the EEG, and a cellular-based understanding is desirable to seek for brain dynamics. In this study, we propose a cellular-based brain model which can simulate EEG characteristics found in actual epileptic patients.
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Keyword(in English) epilepsy / ictal EEG / correlation coefficient / Hodgkin-Huxley equation
Paper # MBE2013-71
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Committee MBE
Conference Date 2013/11/15(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) Epilepsy model and EEG analysis using the correlation between the ictal EEG channels
Sub Title (in English)
Keyword(1) epilepsy
Keyword(2) ictal EEG
Keyword(3) correlation coefficient
Keyword(4) Hodgkin-Huxley equation
1st Author's Name Shumpei WATANABE
1st Author's Affiliation Graduate School of Advanced Integration Science, Chiba University()
2nd Author's Name Yasukuni MORI
2nd Author's Affiliation Graduate School of Advanced Integration Science, Chiba University
3rd Author's Name Yoichi SAITO
3rd Author's Affiliation Research Institute for EEG Analysis
4th Author's Name Hajime HARADA
4th Author's Affiliation Research Institute for EEG Analysis
5th Author's Name Ikuo MATSUBA
5th Author's Affiliation Graduate School of Advanced Integration Science, Chiba University
Date 2013-11-23
Paper # MBE2013-71
Volume (vol) vol.113
Number (no) 314
Page pp.pp.-
#Pages 6
Date of Issue