10.21227/7YA6-EH04
Eduardo Santamaría-Vázquez
Eduardo
Santamaría-Vázquez
0000-0002-7688-4258
Universidad de Valladolid, Spain
Víctor Martínez-Cagigal
Víctor
Martínez-Cagigal
0000-0001-9915-2570
Universidad de Valladolid, Spain
Roberto Hornero
Roberto
Hornero
0000-0002-3822-1787
Universidad de Valladolid, Spain
GIB-UVa ERP-BCI dataset
IEEE DataPort
2020
Biophysiological Signals
Electroencephalography
EEG
brain-computer interfaces
BCI
ERP
P300
2020-09-23
Dataset
Creative Commons Attribution
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 dataset is divided in 3 sets (i.e., training set, validation set and test set) according to Santamaría-Vázquez et al., 2020 (link to article):Training set: contains data from 34 healthy subjectsValidation set: contains data from 8 healthy subjectsTest set: contains data from 31 motor disabled subjectsAdditionally, you will find the results of the original studybroken down by subject, the code to build the deep-learning models used inSantamaría-Vázquez et al., 2020 (i.e., EEG-Inception, EEGNet, DeepConvNet, CNN-BLSTM)and useful scripts to load the dataset or train EEG-Inception.