Dataset of an EEG-based BCI experiment in Virtual Reality and on a Personal Computer

TL;DR

This paper presents a publicly available EEG dataset from an experiment comparing brain responses during P300 tasks on a PC and in virtual reality, including detailed procedures and analysis tools.

Contribution

It provides a novel dataset of EEG recordings in VR and PC settings for P300 BCI research, along with experimental procedures and analysis code.

Findings

Comparable P300 responses in VR and PC conditions

Data supports analysis of physiological and subjective differences

Open dataset facilitates further BCI research in VR environments

Abstract

We describe the experimental procedures for a dataset that we have made publicly available at https://doi.org/10.5281/zenodo.2605204 in mat (Mathworks, Natick, USA) and csv formats. This dataset contains electroencephalographic recordings on 21 subjects doing a visual P300 experiment on PC (personal computer) and VR (virtual reality). The visual P300 is an event-related potential elicited by a visual stimulation, peaking 240-600 ms after stimulus onset. The experiment was designed in order to compare the use of a P300-based brain-computer interface on a PC and with a virtual reality headset, concerning the physiological, subjective and performance aspects. The brain-computer interface is based on electroencephalography (EEG). EEG were recorded thanks to 16 electrodes. The virtual reality headset consisted of a passive head-mounted display, that is, a head-mounted display which does not include any electronics at the exception of a smartphone. This experiment was carried out at GIPSA-lab (University of Grenoble Alpes, CNRS, Grenoble-INP) in 2018, and promoted by the IHMTEK Company (Interaction Homme-Machine Technologie). The study was approved by the Ethical Committee of the University of Grenoble Alpes (Comit{\'e} d'Ethique pour la Recherche Non-Interventionnelle). Python code for manipulating the data is available at https://github.com/plcrodrigues/py.VR.EEG.2018-GIPSA. The ID of this dataset is VR.EEG.2018-GIPSA.