BNCI 2014-008 P300 dataset
Dataset from .
This dataset represents a complete record of P300 evoked potentials using a paradigm originally described by Farwell and Donchin . In these sessions, 8 users with amyotrophic lateral sclerosis (ALS) focused on one out of 36 different characters. The objective in this contest is to predict the correct character in each of the provided character selection epochs.
We included in the study a total of eight volunteers, all naïve to BCI training. Scalp EEG signals were recorded (g.MOBILAB, g.tec, Austria) from eight channels according to 10–10 standard (Fz, Cz, Pz, Oz, P3, P4, PO7 and PO8) using active electrodes (g.Ladybird, g.tec, Austria). All channels were referenced to the right earlobe and grounded to the left mastoid. The EEG signal was digitized at 256 Hz and band-pass filtered between 0.1 and 30 Hz.
Participants were required to copy spell seven predefined words of five characters each (runs), by controlling a P300 matrix speller. Rows and columns on the interface were randomly intensified for 125ms, with an inter stimulus interval (ISI) of 125ms, yielding a 250 ms lag between the appearance of two stimuli (stimulus onset asynchrony, SOA).
In the first three runs (15 trials in total) EEG data was stored to perform a calibration of the BCI classifier. Thus no feedback was provided to the participant up to this point. A stepwise linear discriminant analysis (SWLDA) was applied to the data from the three calibration runs (i.e., runs 1–3) to determine the classifier weights (i.e., classifier coefficients). These weights were then applied during the subsequent four testing runs (i.e., runs 4–7) when participants were provided with feedback.
A. Riccio, L. Simione, F. Schettini, A. Pizzimenti, M. Inghilleri, M. O. Belardinelli, D. Mattia, and F. Cincotti (2013). Attention and P300-based BCI performance in people with amyotrophic lateral sclerosis. Front. Hum. Neurosci., vol. 7:, pag. 732.
L. A. Farwell and E. Donchin, Talking off the top of your head: toward a mental prosthesis utilizing eventrelated brain potentials, Electroencephalogr. Clin. Neurophysiol., vol. 70, n. 6, pagg. 510–523, 1988.
data_path(subject[, path, force_update, …])
Get path to local copy of a subject data.
download([subject_list, path, force_update, …])
Download all data from the dataset.
Return the data correspoonding to a list of subjects.