Zhang Yufeng, Zhang Hongxin, Li Yixuan, Wang Yijun, Gao Xiaorong, Yang Chen
School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China.
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China.
Sci Data. 2025 Jun 23;12(1):1069. doi: 10.1038/s41597-025-05378-x.
Electroencephalogram (EEG)-based biometric emerges as a promising authentication method, offering a novel insight into the future security systems. However, its long-term stability and inter-individual variability necessitate further exploration. This paper presents an event-related potential (ERP) dataset acquired through EEG recordings under rapid serial visual presentation stimulation. The dataset encompasses 200 days of ERP recordings from 15 participants, along with single-session observations from 52 individuals. During the experiment, participants were tasked with identifying a target face to elicit ERP responses. This dataset provides comprehensive and high-quality data for the development of EEG-based identity authentication systems. Additionally, the dataset holds research value for ERP investigation on facial perception and target detection.
基于脑电图（EEG）的生物识别技术作为一种有前途的认证方法出现，为未来的安全系统提供了新的见解。然而，其长期稳定性和个体间变异性需要进一步探索。本文介绍了一个通过快速序列视觉呈现刺激下的脑电图记录获得的事件相关电位（ERP）数据集。该数据集包括15名参与者200天的ERP记录，以及52名个体的单会话观察结果。在实验过程中，参与者的任务是识别目标面孔以引发ERP反应。该数据集为基于EEG的身份认证系统的开发提供了全面且高质量的数据。此外，该数据集对于面部感知和目标检测的ERP研究具有研究价值。
