Mobile BCI dataset of scalp- and ear-EEG with ERP and SSVEP paradigms during standing, walking, and running

We present a mobile dataset of electroencephalography (EEG) from scalp and ear and locomotion sensors collected from 18 subjects moving at different speeds while performing brain-computer interface (BCI) tasks. The experiments were performed under 16 different conditions (2 types of EEG devices x 4 speeds of movements x 2 types of BCI paradigms). The data were collected from 32-channel scalp-EEG, 14-channel ear-EEG, 4-channel electrooculography, and 3 inertial measurement units at the forehead, left ankle, and right ankle simultaneously. The conditions of recording were standing, slow walking, fast walking, and slight running at speeds of 0, 0.8, 1.6, and 2.0 m/sec, respectively. At each speed, two different BCI paradigms, event-related potential (ERP) and steady-state visual evoked potential (SSVEP), were recorded. To evaluate the signal quality, scalp- and ear-EEG data were qualitatively and quantitatively validated at each speed. We expect that the dataset will facilitate BCIs in diverse mobile environments to analyze brain activities and to evaluate the performance quantitatively, so as to broaden the use of practical BCIs.

本研究构建了一套移动式脑电数据集，该数据集采集了18名受试者在以不同速度运动并执行脑机接口（brain-computer interface, BCI）任务时的头皮与耳部脑电图（electroencephalography, EEG）及运动传感器数据。实验共设置16种不同的实验条件，覆盖2类EEG采集设备、4种运动速度与2类BCI范式。本次采集的数据包含同时记录的32通道头皮EEG、14通道耳部EEG、4通道眼电图（electrooculography, EOG），以及分别安装于前额、左脚踝与右脚踝的3个惯性测量单元（inertial measurement unit）采集的运动数据。实验中的运动状态分为静站、慢走、快走与轻度跑步，对应运动速度分别为0、0.8、1.6与2.0 m/秒。在每一种运动速度下，均会采集两类BCI范式的数据：事件相关电位（event-related potential, ERP）与稳态视觉诱发电位（steady-state visual evoked potential, SSVEP）。为验证信号质量，研究人员针对每一种运动速度下的头皮EEG与耳部EEG数据开展了定性与定量分析验证。本数据集旨在助力多样化移动环境下的BCI研究，用于脑活动分析与系统性能定量评估，进而拓展实用型脑机接口的应用边界。