Zhang Shangen, Wang Yijun, Zhang Lijian, Gao Xiaorong
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China.
Beijing Key Laboratory of Knowledge Engineering for Materials Science, Beijing, China.
Front Neurosci. 2020 Oct 2;14:568000. doi: 10.3389/fnins.2020.568000. eCollection 2020.
This paper reports on a benchmark dataset acquired with a brain-computer interface (BCI) system based on the rapid serial visual presentation (RSVP) paradigm. The dataset consists of 64-channel electroencephalogram (EEG) data from 64 healthy subjects (sub1,…, sub64) while they performed a target image detection task. For each subject, the data contained two groups ("A" and "B"). Each group contained two blocks, and each block included 40 trials that corresponded to 40 stimulus sequences. Each sequence contained 100 images presented at 10 Hz (10 images per second). The stimulus images were street-view images of two categories: target images with human and non-target images without human. Target images were presented randomly in the stimulus sequence with a probability of 1∼4%. During the stimulus presentation, subjects were asked to search for the target images and ignore the non-target images in a subjective manner. To keep all original information, the dataset was the raw continuous data without any processing. On one hand, the dataset can be used as a benchmark dataset to compare the algorithms for target identification in RSVP-based BCIs. On the other hand, the dataset can be used to design new system diagrams and evaluate their BCI performance without collecting any new data through offline simulation. Furthermore, the dataset also provides high-quality data for characterizing and modeling event-related potentials (ERPs) and steady-state visual evoked potentials (SSVEPs) in RSVP-based BCIs. The dataset is freely available from http://bci.med.tsinghua.edu.cn/download.html.
本文报道了一个通过基于快速序列视觉呈现（RSVP）范式的脑机接口（BCI）系统获取的基准数据集。该数据集由64名健康受试者（sub1，…，sub64）在执行目标图像检测任务时的64通道脑电图（EEG）数据组成。对于每个受试者，数据包含两组（“A”和“B”）。每组包含两个块，每个块包括40次试验，对应40个刺激序列。每个序列包含以10Hz（每秒10张图像）呈现的100张图像。刺激图像为两类街景图像：有人的目标图像和无人的非目标图像。目标图像在刺激序列中以1%至4%的概率随机呈现。在刺激呈现过程中，要求受试者以主观方式搜索目标图像并忽略非目标图像。为保留所有原始信息，该数据集为未经任何处理的原始连续数据。一方面，该数据集可作为基准数据集，用于比较基于RSVP的脑机接口中目标识别算法。另一方面，该数据集可用于设计新的系统图，并通过离线模拟评估其脑机接口性能，而无需收集任何新数据。此外，该数据集还为表征和建模基于RSVP的脑机接口中的事件相关电位（ERP）和稳态视觉诱发电位（SSVEP）提供了高质量数据。该数据集可从http://bci.med.tsinghua.edu.cn/download.html免费获取。
