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Authentication using c-VEP evoked in a mild-burdened cognitive task

In recent years, more and more researchers are devoting themselves to the studies about authentication based on biomarkers. Among a wide variety of biomarkers, code-modulated visual evoked potential (c-VEP) has attracted increasing attention due to its significant role in the field of brain-computer...

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Detalles Bibliográficos
Autores principales: Huang, Zhihua, Liao, Zequan, Ou, Guojie, Chen, Lijun, Zhang, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10512977/
https://www.ncbi.nlm.nih.gov/pubmed/37746053
http://dx.doi.org/10.3389/fnhum.2023.1240451
Descripción
Sumario:In recent years, more and more researchers are devoting themselves to the studies about authentication based on biomarkers. Among a wide variety of biomarkers, code-modulated visual evoked potential (c-VEP) has attracted increasing attention due to its significant role in the field of brain-computer interface. In this study, we designed a mild-burdened cognitive task (MBCT), which can check whether participants focus their attention on the visual stimuli that evoke c-VEP. Furthermore, we investigated the authentication based on the c-VEP evoked in the cognitive task by introducing a deep learning method. Seventeen participants were recruited to take part in the MBCT experiments including two sessions, which were carried out on two different days. The c-VEP signals from the first session were extracted to train the authentication deep models. The c-VEP data of the second session were used to verify the models. It achieved a desirable performance, with the average accuracy and F1 score, respectively, of 0.92 and 0.89. These results show that c-VEP carries individual discriminative characteristics and it is feasible to develop a practical authentication system based on c-VEP.