moabb.datasets.BNCI2014_009#

class moabb.datasets.BNCI2014_009[source]#

BNCI 2014-009 P300 dataset.

PapersWithCode leaderboard: https://paperswithcode.com/dataset/bnci2014-009-moabb-1

Dataset summary

#Subj	10
#Chan	16
#Trials / class	1440 NT / 288 T
Trials length	0.8 s
Freq	256 Hz
#Sessions	3

Participants

Population: healthy
Age: 26.82 years
BCI experience: previous experience with P300-based BCIs

Equipment

Amplifier: g.tec
Electrodes: Ag/AgCl
Montage: 10-10
Reference: earlobe

Preprocessing

Data state: filtered
Bandpass filter: 0.1-20 Hz
Steps: bandpass filtering
Re-reference: car

Data Access

DOI: 10.1080/00140139.2012.661084

Experimental Protocol

Paradigm: p300
Feedback: none
Stimulus: oddball

Dataset from [1].

Dataset Description

This dataset contains EEG data from 10 subjects using a P300 speller system with both grid speller and geo-speller paradigms. This loader includes only the grid speller data.

Participants

10 healthy subjects

Recording Details

Channels: 16 EEG channels
Sampling rate: 256 Hz
Reference: Linked mastoids

References

[1]

Riccio, A., Simione, L., Schettini, F., Pizzimenti, A., Inghilleri, M., Belardinelli, M. O., & Mattia, D. (2013). Attention and P300-based BCI performance in people with amyotrophic lateral sclerosis. Frontiers in human neuroscience, 7, 732. https://doi.org/10.3389/fnhum.2013.00732

Notes

Note

BNCI2014_009 was previously named BNCI2014009. BNCI2014009 will be removed in version 1.1.

Added in version 0.4.0.

Examples using `moabb.datasets.BNCI2014_009`#

Within Session P300

MNE Epochs-based pipelines

Within Session P300 with Learning Curve

moabb.datasets.BNCI2014_009#

Examples using moabb.datasets.BNCI2014_009#

Examples using `moabb.datasets.BNCI2014_009`#