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BED: A new dataset for EEG-based biometrics

Arnau-González, Pablo and Katsigiannis, Stamos and Arevalillo-Herráez, Miguel and Ramzan, Naeem (2021) 'BED: A new dataset for EEG-based biometrics.', IEEE Internet of things journal., 8 (15). pp. 12219-12230.


Various recent research works have focused on the use of electroencephalography (EEG) signals in the field of biometrics. However, advances in this area have somehow been limited by the absence of a common testbed that would make it possible to easily compare the performance of different proposals. In this work, we present a dataset that has been specifically designed to allow researchers to attempt new biometric approaches that use EEG signals captured by using relatively inexpensive consumer-grade devices. The proposed dataset has been made publicly accessible and can be downloaded from It contains EEG recordings and responses from 21 individuals, captured under 12 different stimuli across three sessions. The selected stimuli included traditional approaches, as well as stimuli that aim to elicit concrete affective states, in order to facilitate future studies related to the influence of emotions on the EEG signals in the context of biometrics. The captured data were checked for consistency and a performance study was also carried out in order to establish a baseline for the tasks of subject verification and identification.

Item Type:Article
Full text:(AM) Accepted Manuscript
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Publisher statement:© 2021 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 collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Date accepted:18 February 2021
Date deposited:26 February 2021
Date of first online publication:24 February 2021
Date first made open access:26 February 2021

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