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

本数据集由高丽大学脑与认知工程系创建，包含24名参与者在站立、慢走、快走和轻微跑步状态下的头皮脑电图（EEG）和耳部脑电图数据。数据集涵盖了事件相关电位（ERP）和稳态视觉诱发电位（SSVEP）两种脑机接口范式，旨在分析移动环境中的人脑活动并量化评估脑机接口性能。数据收集使用了32通道头皮EEG、14通道耳部EEG、4通道眼电图和27通道惯性测量单元，记录了不同速度下的脑电活动，以支持移动环境中脑机接口技术的研究与开发。

This dataset was created by the Department of Brain and Cognitive Engineering, Korea University. It contains scalp and ear electroencephalogram (EEG) data from 24 participants during four movement states: standing, slow walking, fast walking, and gentle running. The dataset covers two brain-computer interface (BCI) paradigms: event-related potentials (ERP) and steady-state visually evoked potentials (SSVEP), and is intended to analyze human brain activity in mobile environments and quantitatively evaluate BCI performance. Data collection was conducted using a 32-channel scalp EEG system, 14-channel ear EEG setup, 4-channel electrooculogram (EOG), and 27-channel inertial measurement unit (IMU). The recordings capture brain electrical activity across different movement speeds, supporting research and development of BCI technologies in mobile environments.

搜集汇总

背景与挑战

背景概述

该数据集是由高丽大学采集的移动脑机接口数据集，包含24名参与者在站立、行走和跑步四种运动状态下的头皮与耳部脑电图数据，同时记录了眼动和运动惯性数据。数据集采用事件相关电位和稳态视觉诱发电位两种实验范式，旨在研究移动环境中的人脑活动并评估脑机接口性能，为移动脑机接口技术开发提供多模态数据支持。