moabb.datasets.Cattan2019_VR#

class moabb.datasets.Cattan2019_VR(virtual_reality=True, screen_display=True, subjects=None, sessions=None, **kwargs)[source]#

Dataset of an EEG-based BCI experiment in Virtual Reality using P300.

PapersWithCode leaderboard: https://paperswithcode.com/dataset/cattan2019-vr-moabb-1

Dataset summary

#Subj

21

#Chan

16

#Trials / class

600 NT / 120 T

Trials length

1 s

Freq

512 Hz

#Sessions

2

Participants

  • Population: healthy

  • Age: 26.38 (range: 19-44) years

  • BCI experience: varied gaming experience: some played video games occasionally, some played First Person Shooters; varied VR experience from none to repetitive

Equipment

  • Amplifier: g.USBamp (g.tec, Schiedlberg, Austria)

  • Electrodes: wet electrodes

  • Montage: 10-10

  • Reference: right earlobe

Preprocessing

  • Data state: raw EEG with software tagging via USB (note: tagging introduces jitter and latency - mean 38ms in PC, 117ms in VR)

  • Notes: mean tagging latency: ~38 ms in PC, ~117 ms in VR due to different hardware/software setup; these latencies should be used to correct ERPs

Data Access

Experimental Protocol

  • Paradigm: p300

  • Feedback: random visual feedback (70% expected accuracy)

  • Stimulus: flashing white crosses in 6x6 matrix

Found an issue with this dataset?

If you encounter any problems with this dataset (missing files, incorrect metadata, loading errors, etc.), please let us know!

Report an Issue on GitHub

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 [1]. This dataset contains electroencephalographic recordings on 21 subjects doing a visual P300 experiment on non-VR (PC display) 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 at the exception of a smartphone. A full description of the experiment is available at https://hal.archives-ouvertes.fr/hal-02078533.

See the example plot_vr_pc_p300_different_epoch_size to compare the performance between PC and VR.

Parameters:

  • virtual_reality (bool (default False)) – if True, return runs corresponding to P300 experiment on virtual reality.

  • screen_display (bool (default True)) – if True, return runs corresponding to P300 experiment on personal computer.

Notes

Note

Cattan2019_VR was previously named VirtualReality. VirtualReality will be removed in version 1.1.

Added in version 0.5.0.

References

[1]

G. Cattan, A. Andreev, P. L. C. Rodrigues, and M. Congedo (2019). Dataset of an EEG-based BCI experiment in Virtual Reality and on a Personal Computer. Research Report, GIPSA-lab; IHMTEK. https://doi.org/10.5281/zenodo.2605204

Added in version 0.5.0.

data_path(subject, path=None, force_update=False, update_path=None, verbose=None)[source]#

Get path to local copy of a subject data.

Parameters:

  • subject (int) – Number of subject to use

  • path (None | str) – Location of where to look for the data storing location. If None, the environment variable or config parameter MNE_DATASETS_(dataset)_PATH is used. If it doesn’t exist, the “~/mne_data” directory is used. If the dataset is not found under the given path, the data will be automatically downloaded to the specified folder.

  • force_update (bool) – Force update of the dataset even if a local copy exists.

  • update_path (bool | None Deprecated) – If True, set the MNE_DATASETS_(dataset)_PATH in mne-python config to the given path. If None, the user is prompted.

  • verbose (bool, str, int, or None) – If not None, override default verbose level (see mne.verbose()).

Returns:

path – Local path to the given data file. This path is contained inside a list of length one, for compatibility.

Return type:

list of str

Examples using moabb.datasets.Cattan2019_VR#

Tutorial 5: Creating a dataset class

Tutorial 5: Creating a dataset class

Changing epoch size in P300 VR dataset

Changing epoch size in P300 VR dataset