moabb.datasets.Dreyer2023#

class moabb.datasets.Dreyer2023[source]#

Class for Dreyer2023 dataset management. MI dataset.

Dataset summary

#Subj

#Chan

#Classes

#Trials / class

Trial length(s)

Freq(Hz)

#Session

#Runs

Total_trials

87

27

2

20

5

512

1

6

20880

Dataset description

“A large EEG database with users’ profile information for motor imagery Brain-Computer Interface research” [1] [2]

Data collectorsAppriou Aurélien; Caselli Damien; Benaroch Camille;

Yamamoto Sayu Maria; Roc Aline; Lotte Fabien; Dreyer Pauline; Pillette Léa

Data manager : Dreyer Pauline Project leader : Lotte Fabien Project members : Rimbert Sébastien; Monseigne Thibaut

Dataset Dreyer2023 contains concatenated datasets Dreyer2023A, Dreyer2023B and Dreyer2023C.

Experiments were conducted by six experimenters. In addition, for each recording the following pieces of information are provided: subject’s demographic, personality and cognitive profiles, the OpenViBE experimental instructions and codes, and experimenter’s gender.

The experiment is designed for the investigation of the impact of the participant’s and experimenter’s gender on MI BCI performance [1].

A recording contains open and closed eyes baseline recordings and 6 runs of the MI experiments. First 2 runs (acquisition runs) were used to train system and the following 4 runs (training runs) to train the participant. Each run contained 40 trials [1].

Each trial was recorded as follows [1]:

  • t=0.00s cross displayed on screen

  • t=2.00s acoustic signal announced appearance of a red arrow

  • t=3.00s a red arrow appears (subject starts to perform task)

  • t=4.25s the red arrow disappears

  • t=4.25s the feedback on performance is given in the form of a blue bar

    with update frequency of 16 Hz

  • t=8.00s cross turns off (subject stops to perform task)

EEG signals [1]:

  • recorded with 27 electrodes, namely: Fz, FCz, Cz, CPz, Pz, C1, C3, C5, C2, C4, C6, F4, FC2, FC4, FC6, CP2, CP4, CP6, P4, F3, FC1, FC3, FC5, CP1, CP3, CP5, P3 (10-20 system), referenced to the left earlobe.

EOG signals [1]:

  • recorded with 3 electrodes, namely: EOG1, EOG2, EOG3 placed below, above and on the side of one eye.

EMG signals [1]:

  • recorded with 2 electrodes, namely: EMGg, EMGd placed 2.5cm below the skinfold on each wrist.

Demographic and biosocial information includes:

  • gender, birth year, laterality

  • vision, vision assistance

  • familiarity to cognitive science or neurology, level of education

  • physical activity, meditation

  • attentional, neurological, psychiatrics symptoms

Personality and the cognitive profile [1]:

  • evaluated via 5th edition of the 16 Personality Factors (16PF5) test

  • and mental rotation test

  • index of learning style

Pre and post experiment questionnaires [1]:

  • evaluation of pre and post mood, mindfulness and motivational states

The online OpenViBE BCI classification performance [1]:

  • only performance measure used to give the feedback to the participants

References

[1] (1,2,3,4,5,6,7,8,9,10)

Pillette, L., Roc, A., N’kaoua, B., & Lotte, F. (2021). Experimenters’ influence on mental-imagery based brain-computer interface user training. International Journal of Human-Computer Studies, 149, 102603.

[2]

Benaroch, C., Yamamoto, M. S., Roc, A., Dreyer, P., Jeunet, C., & Lotte, F. (2022). When should MI-BCI feature optimization include prior knowledge, and which one?. Brain-Computer Interfaces, 9(2), 115-128.

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