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- W3110511602 abstract "Electroencephalogram (EEG), measuring brain activities, is believed to be a carrier of brain activity-based biometric. Researchers have explored all kind of approaches to extracting biometric from EEG for individual identification. An emerging trend is to use code-modulated visual potentials (c-VEP) in the EEG-based method to enhance the performance of this kind of individual identification. In this study, we proposed a stimulus mode with left-and-right balance to evoke c-VEPs for individual identification. In the mode, the two panes on the screen, one in the left visual field and another in the right visual field, flashed at the same time under the control of two different m-sequences. The subjects were guided to gaze at one of the panes, one half of trials for the left, the other half for the right. The left and right c-VEPs of subjects were integrated to construct subject identity templates. State-of-the-art detection algorithms in VEP brain-computer interfaces were used to match the c-VEP templates with left-and-right balance for individual identification. We recruited 20 subjects to participate in our experiments and achieved a 92.5% correct recognition rate on their EEG datasets. Our further analysis on the mismatches revealed that the biometric of c-VEPs with left-and-right balance is stable." @default.
- W3110511602 created "2020-12-07" @default.
- W3110511602 creator A5032594969 @default.
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- W3110511602 date "2020-10-17" @default.
- W3110511602 modified "2023-09-26" @default.
- W3110511602 title "Individual identification using code-modulated visual potentials with left-and-right balance" @default.
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- W3110511602 doi "https://doi.org/10.1109/cisp-bmei51763.2020.9263506" @default.
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