GIB-UVa ERP-BCI dataset

This dataset contains EEG signals from 73 subjects (42 healthy; 31 disabled) using an ERP-based speller to control differentbrain-computer interface (BCI) applications. The demographics of the dataset can be found in info.txt.Additionally, you will find the results of the original studybroken down by subject, the code to build the deep-learning models used in[1] (i.e., EEG-Inception, EEGNet, DeepConvNet, CNN-BLSTM)and a script to load the dataset.[1]Santamaría-Vázquez, E., Martínez-Cagigal, V., Vaquerizo-Villar, F., Hornero, R. (2020). EEG-Inception: A Novel Deep Convolutional Neural Network for Assistive ERP-based Brain-Computer Interfaces.IEEE Transactions on Neural Systems and Rehabilitation Engineering.https://doi.org/10.1109/TNSRE.2020.3048106

本数据集包含73名受试者的脑电图(EEG)信号，其中42名为健康个体，31名为残障个体；所有受试者均通过基于事件相关电位(ERP)的拼写器来操控各类脑机接口(BCI)应用。
本数据集的人口统计学信息可在info.txt文件中查阅。
此外，您还可获取按受试者分项的原始研究结果、文献[1]中所用深度学习模型（即EEG-Inception、EEGNet、DeepConvNet、CNN-BLSTM）的构建代码，以及用于加载本数据集的脚本。
[1] Santamaría-Vázquez, E., Martínez-Cagigal, V., Vaquerizo-Villar, F., Hornero, R. (2020). EEG-Inception：一种用于辅助型基于事件相关电位脑机接口的新型深度卷积神经网络. 《IEEE神经系统与康复工程汇刊》(IEEE Transactions on Neural Systems and Rehabilitation Engineering). https://doi.org/10.1109/TNSRE.2020.3048106