RT info:eu-repo/semantics/article
T1 Brainprint based on functional connectivity and asymmetry indices of brain regions: A case study of biometric person identification with non-expensive electroencephalogram headsets.
A1 Gómez González, José Francisco
A1 Ortega Rodríguez, Jordan
A1 Martín Chinea, Kevin
A1 Pereda de Pablo, Ernesto
A2 Ingeniería Industrial
K1 Biometrics brain‐computer interface (BCI)
K1 Classification
K1 Electroencephalogram (EEG)
AB Brain‐computer interface applications for biometric person identification have increasedtheir interest in recent years since they are potentially more secure and more difficult tocounterfeit than traditional biometric techniques. However, it is necessary to consider how brain waves are acquired for this purpose, not only in terms of efficiency but also of practical comfort for the user and the affordability degree of the biosignal acquisition device so that their everyday application can become a realistic possibility. In this context,this paper presents the capabilities of using a non‐expensive wireless electroencephalogram (EEG) device to extract spectral‐related and functional connectivity information of brain activity. The proposed method achieved a sufficient biometric identification with two datasets of 13 and 109 subjects when comparing the performance of a sizeable classification algorithm set. In addition, a novel feature in EEG biometric identification,called asymmetry index, is introduced here. Furthermore, this is the first study in this fieldto consider the effect of the time‐lapse between different recording sessions on the system's behaviour when using a low‐cost EEG device with identification accuracy rates of up to 100%.
SN 2047-4938
YR 2023
FD 2023
LK http://riull.ull.es/xmlui/handle/915/39049
UL http://riull.ull.es/xmlui/handle/915/39049
LA en
DS Repositorio institucional de la Universidad de La Laguna
RD 24-nov-2024