GIB-UVa ERP-BCI dataset

  1. Santamaría-Vázquez, Eduardo 1
  2. Martínez-Cagigal, Víctor 1
  3. Hornero, Roberto 1
  1. 1 Universidad de Valladolid, Spain

Verleger: IEEE DataPort

Datum der Publikation: 2021

Art: Dataset

CC BY 4.0

DOI: 10.21227/HT59-QQ50 lock_openOpen Access editor

Zusammenfassung

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