moabb.datasets.BNCI2014_009#
- class moabb.datasets.BNCI2014_009(subjects=None, sessions=None)[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: 26.8 years
BCI experience: experienced
Equipment
Amplifier: g.USBamp
Electrodes: Ag/AgCl
Montage: 10-10
Reference: linked earlobes
Preprocessing
Data state: preprocessed
Bandpass filter: 0.1-20 Hz
Steps: bandpass filtering
Re-reference: linked earlobes
Notes: EEG acquired using g.USBamp amplifier (g.Tec, Austria), digitized at 256 Hz
Data Access
DOI: 10.1088/1741-2560/11/3/035008
Repository: BNCI Horizon
Experimental Protocol
Paradigm: p300
Task type: spelling
Feedback: none
Stimulus: visual_intensification
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!
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_009was previously namedBNCI2014009.BNCI2014009will be removed in version 1.1.Added in version 0.4.0.
Examples using moabb.datasets.BNCI2014_009#
Riemannian Artifact Rejection as a Pre-processing Step
