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There has been an increasing attention on Electroencephalograph (EEG) based personal identification over the last decade. Most existing methods address this problem by Euclidean metric based Nearest Neighbor (NN) search. However, under various recording conditions, simple Euclidean distance cannot model the similarity relations between EEG signals precisely. To overcome this drawback, a local metric...
Previous studies have proved the reliability of using EEG signal as a biometric modality. Nowadays, some portable EEG recording systems are emerged as the peripheral devices to allow people use their EEG to play computer games or control toys, and it was also demonstrated that the single-channel EEG signals recorded by the portable equipment can be used for personal identification. However, unlike...
This paper proposes a dual-biometric-modality personal identification system, which has both outstanding identification performance and effective anti-spoofing property. This dual-modality system represents the first effort to fuse the conventional fingerprint with a novel biométrie modality-Electroencephalogram (EEG). The fusion of these two modalities is achieved at the matching score level. Experimental...
Although the concept of using brain waves, e.g. Electroencephalogram (EEG), for personal identification has been validated in several studies, some unanswered practical and theoretical questions prevent this technology from further development for commercialization. Based on a well-designed personal identification experiment using EEG recordings, this study addressed three of these questions, which...
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