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BED: A new dataset for EEG-based biometrics

Arnau-González, Pablo; Katsigiannis, Stamos; Arevalillo-Herráez, Miguel; Ramzan, Naeem

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Authors

Pablo Arnau-González

Miguel Arevalillo-Herráez

Naeem Ramzan



Abstract

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 https://doi.org/10.5281/zenodo.4309471. 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.

Citation

Arnau-González, P., Katsigiannis, S., Arevalillo-Herráez, M., & Ramzan, N. (2021). BED: A new dataset for EEG-based biometrics. IEEE Internet of Things Journal, 8(15), 12219-12230. https://doi.org/10.1109/jiot.2021.3061727

Journal Article Type Article
Acceptance Date Feb 18, 2021
Online Publication Date Feb 24, 2021
Publication Date Aug 1, 2021
Deposit Date Feb 24, 2021
Publicly Available Date Feb 26, 2021
Journal IEEE Internet of Things Journal
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 8
Issue 15
Pages 12219-12230
DOI https://doi.org/10.1109/jiot.2021.3061727

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