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Introduction of Fractal Dimension Feature and Reduction of Calculation Amount in Person Authentication Using Evoked EEG by Ultrasound
https://repository.lib.tottori-u.ac.jp/records/7044
https://repository.lib.tottori-u.ac.jp/records/70447d1f409e-d7ef-473c-8d64-f0e7749b92f1
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
TENCON2020_Mukai.pdf (917.1 kB)
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| Item type | 会議発表論文 / Conference Paper(1) | |||||
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| 公開日 | 2020-11-20 | |||||
| タイトル | ||||||
| タイトル | Introduction of Fractal Dimension Feature and Reduction of Calculation Amount in Person Authentication Using Evoked EEG by Ultrasound | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 主題 | Biometric authentication, Electroencephalogram(EEG), Ultrasound, Fractal dimension, Calculation amount Biometric authentication(en), Electroencephalogram(EEG)(en), Ultrasound(en), Fractal dimension(en), Calculation amount(en) |
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| 資源タイプ | ||||||
| 資源タイプ | conference paper | |||||
| 著者 |
中西, 功
× 中西, 功× Kotaro, Mukai |
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| 著者所属（英） | ||||||
| 言語 | en | |||||
| 値 | Graduate School of Sustainability Science Tottori University | |||||
| 著者所属（英） | ||||||
| 言語 | en | |||||
| 値 | Faculty of Engineering, Tottori University | |||||
| 抄録 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | The aim of this study is to authenticate individuals using an electroencephalogram (EEG) evoked by a stimulus. EEGs are highly confidential and enable continuous authentication during the use of or access to the given information or service. However, perceivable stimulation distracts the users from the activity they are carrying out while using the service. Therefore, ultrasound stimuli were chosen for EEG evocation. In our previous study, an Equal Error Rate (EER) of 0 % was achieved; however, there were some features which had not been evaluated. In this paper, we introduce a new type of feature, namely fractal dimension, as a nonlinear feature, and evaluate its verification performance on its own and in combination with other conventional features. As a result, an EER of 0 % was achieved when using five features and 14 electrodes, which accounted for 70 support vector machine (SVM) models. However, the construction of the 70 SVM models required extensive calculations. Thus, we reduced the number of SVM models to 24 while maintaining an EER = 0 %. | |||||
| 書誌情報 |
Proceedings of the 2020 IEEE Region 10 Conference (TENCON2020) en : Proceedings of the 2020 IEEE Region 10 Conference (TENCON2020) 発行日 2020-11 |
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| 権利 | ||||||
| 権利情報 | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collec | |||||
| 情報源 | ||||||
| 関連名称 | K. Mukai, I Nakanishi. Introduction of Fractal Dimension Feature and Reduction of Calculation Amount in Person Authentication Using Evoked EEG by Ultrasound. Proceedings of the 2020 IEEE Region 10 Conference (TENCON2020). 2020 | |||||
| 著者版フラグ | ||||||
| 出版タイプ | AM | |||||
