moabb.datasets.BNCI2015_001

class moabb.datasets.BNCI2015_001

BNCI 2015-001 Motor Imagery dataset.

PapersWithCode leaderboard: https://paperswithcode.com/dataset/bnci2015-001-moabb-1

Dataset summary

#Subj	12
#Chan	13
#Classes	2
#Trials / class	200
Trials length	5 s
Freq	512 Hz
#Sessions	3
#Runs	1
Total_trials	14400

Participants

• Population: ALS

• Age: 24.8 years

• Handedness: all right-handed

• BCI experience: naive

Equipment

• Amplifier: g.tec

• Electrodes: active electrode

• Montage: 10-20

• Reference: Car

Preprocessing

• Data state: filtered

• Bandpass filter: 0.5-100 Hz

• Steps: bandpass filter, notch filter

• Re-reference: car

Data Access

• DOI: 10.1109/tnsre.2012.2189584

Experimental Protocol

• Paradigm: imagery

• Feedback: none

• Stimulus: cursor_feedback

Dataset from [1].

Dataset Description

This dataset contains EEG data from 12 subjects performing two-class motor imagery tasks (left vs right hand). Each subject participated in multiple sessions, with some subjects having three sessions.

Participants

• 12 healthy subjects

• Gender: not specified

• Age: not specified

Recording Details

• Channels: 13 EEG electrodes

• Sampling rate: 512 Hz

• Reference: not specified

References

[1]

Faller, J., Scherer, R., Costa, U., Opisso, E., Medina, J., Muller-Putz, G. R. (2014). A co-adaptive brain-computer interface for end users with severe motor impairment. PLOS ONE, 9(7), e101168. https://doi.org/10.1371/journal.pone.0101168

Notes

Note

BNCI2015_001 was previously named BNCI2015001. BNCI2015001 will be removed in version 1.1.

Added in version 0.4.0.