moabb.datasets.Cattan2019_PHMD#
- class moabb.datasets.Cattan2019_PHMD(subjects=None, sessions=None)[source]#
Passive Head Mounted Display with Music Listening dataset [1].
Dataset summary
#Subj
12
#Chan
16
#Classes
2
Trials length
60 s
Freq
512 Hz
#Sessions
1
#Blocks / class
5
Participants
Population: healthy
Age: 26.25 years
Equipment
Amplifier: g.USBamp
Electrodes: wet electrodes
Montage: 10-10
Reference: right earlobe
Preprocessing
Data state: raw, unfiltered
Notes: Data were acquired with no digital filter. No Faraday cage used to mimic real-world usage.
Data Access
DOI: 10.5281/zenodo.2617084
Data URL: https://doi.org/10.5281/zenodo.2617084
Repository: Zenodo
Experimental Protocol
Paradigm: rstate
Feedback: none
Stimulus: visual marker (purple marker on smartphone screen)
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We describe the experimental procedures for a dataset that we have made publicly available at https://doi.org/10.5281/zenodo.2617084 in mat (Mathworks, Natick, USA) and csv formats. This dataset contains electroencephalographic recordings of 12 subjects listening to music with and without a passive head-mounted display, that is, a head-mounted display which does not include any electronics at the exception of a smartphone. The electroencephalographic headset consisted of 16 electrodes. Data were recorded during a pilot experiment taking place in the GIPSA-lab, Grenoble, France, in 2017 (Cattan and al, 2018). The ID of this dataset is PHMDML.EEG.2017-GIPSA.
full description of the experiment https://hal.archives-ouvertes.fr/hal-02085118
Link to the data https://doi.org/10.5281/zenodo.2617084
Authors Principal Investigator: Eng. Grégoire Cattan Technical Supervisors: Eng. Pedro L. C. Rodrigues Scientific Supervisor: Dr. Marco Congedo
ID of the dataset PHMDML.EEG.2017-GIPSA
Notes
Note
Cattan2019_PHMDwas previously namedHeadMountedDisplay.HeadMountedDisplaywill be removed in version 1.1.Added in version 1.0.0.
References
[1]G. Cattan, P. L. Coelho Rodrigues, and M. Congedo, ‘Passive Head-Mounted Display Music-Listening EEG dataset’, Gipsa-Lab ; IHMTEK, Research Report 2, Mar. 2019. doi: 10.5281/zenodo.2617084.
- 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)_PATHis 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: