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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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Dataset of an EEG-based BCI experiment in Virtual Reality and on a Personal Computer

Authors: Cattan, Grégoire; Andreev, Anton; Rodrigues, Pedro L. C.; Congedo, Marco;

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

Abstract

Summary: 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 data 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 with the exception of a smartphone. A full description of the experiment is available at https://hal.archives-ouvertes.fr/hal-02078533. 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 (Comité 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. Full description of the experiment and dataset: https://hal.archives-ouvertes.fr/hal-02078533 An analysis of the experiment: https://hal.archives-ouvertes.fr/hal-02464023 Principal Investigator: Eng. Grégoire Cattan Technical Supervisors: Eng. Anton Andreev, Eng. Pedro L. C. Rodrigues Scientific Supervisor: Dr. Marco Congedo ID of the dataset: VR.EEG.2018-GIPSA

Keywords

Experiment, Electroencephalography (EEG), P300, Brain-Computer Interface (BCI), Virtual Reality (VR)

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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