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Authors |
Nakashima, Hirotomo
Graduate School of Sustainability Sciences Tottori University
Shindo, Yoshiaki
Graduate School of Sustainability Sciences Tottori University
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Keywords | biometrics
EEG
imperceptible vibration stimuli
EER
SVM
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Abstract | In this study, we examine electroencephalogram (EEG) biometric information that can be detected continuously with high confidentiality to realize personal verification using the evoked EEG when presented with an imperceptible vibration stimulus. Considering the survey of conventional studies on brainwaves evoked by perceptible vibration stimulation, we determined that to use the evoked EEG, including the immediately response after the stimulus is effective in verification. Therefore, we introduce a method for repeating the stimulus presentation over a short time. In addition, to improve the verification performance, we introduce support vector machine (SVM). Furthermore, we evaluated the verification performance and obtained an equal error rate of 11%.
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Publisher | IEEE xplore
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Content Type |
Conference Paper
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Journal Title | Proc. of the 20th International Symposium on Communications and Information Technologies (ISCIT 2021)
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Current Journal Title |
Proc. of the 20th International Symposium on Communications and Information Technologies (ISCIT 2021)
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Published Date | 2021
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Publisher-DOI | |
Text Version |
Author
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Rights | © 2021 IEEE xplore
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Citation | Nakashima Hirotomo, Shindo Yoshiaki, Nakanishi Isao. Performance Improvement in User Verification Using Evoked Electroencephalogram by Imperceptible Vibration Stimuli. Proc. of the 20th International Symposium on Communications and Information Technologies (ISCIT 2021), 2021.
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Department |
Faculty of Engineering/Graduate School of Engineering
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Language |
English
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