Re-hosted EEG data from Pressel Coretto, Gareis, and Rufiner (2017), originally distributed through Google Drive (file id 0By7apHbIp8ENZVBLRFVlSFhzbHc) as an open-access companion to the SIPAIM/SPIE proceedings paper. Repackaged into per-subject ZIP archives for easier programmatic access from the MOABB benchmarking framework. Paper G. A. Pressel Coretto, I. E. Gareis, and H. L. Rufiner, “Open access database of EEG signals recorded during imagined speech,” in Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 2017.DOI: 10.1117/12.2255697 Paradigm 11-class imagined speech of Spanish phonemes and directional commands: Vowels: /a/, /e/, /i/, /o/, /u/ (stim codes 1-5) Directional commands: arriba (up), abajo (down), adelante (forward), atrás (back), derecha (right), izquierda (left) (stim codes 6-11) Two modalities were recorded per stimulus: imagined speech (modality code 1) and pronounced speech (modality code 2). The MOABB adapter loads the imagined condition by default. Each trial is 4 seconds at 1024 Hz (4096 samples). Participants 15 Argentinian volunteers (7 female, 8 male, ages 24-28) Institution: Universidad Nacional de Entre Ríos (Argentina) Recording setup ParameterValueAmplifierGrass 8-18-36ADCDataTranslation DT9816Channels6 (F3, F4, C3, C4, P3, P4)Sampling rate1024 HzBandpass2–45 HzFile formatMATLAB (.mat) File structure 15 per-subject ZIP files (S01.zip–S15.zip). Each contains a single MATLAB file renamed from the original S{NN}_EEG.mat to sub-{NN}_eeg.mat: S01.zip sub-01_eeg.mat S02.zip sub-02_eeg.mat ... S15.zip sub-15_eeg.mat README.md ← top-level, stimulus codes and channels The .mat files are bit-identical to the originals; only the filename was changed to adopt the MOABB subject-ID convention. Data format Each .mat file contains an EEG variable of shape (n_trials, 6 * 4096 + 3). The first 24576 columns are flattened channel-first EEG samples; the last three columns are labels: [modality, stimulus_code, artifact_flag]. Loading with MOABB from moabb.datasets import Pressel2016 from moabb.paradigms import MotorImagery dataset = Pressel2016() paradigm = MotorImagery( events=["vowel_a", "vowel_e", "vowel_i"], ) X, y, metadata = paradigm.get_data(dataset=dataset, subjects=[1]) Re-hosting rationale The original Google Drive share relies on the gdown library and a legacy resourcekey token. Both are fragile: Google Drive can quota-block downloads, change its confirm-token protocol, or revoke resource keys (we observed all three modes of failure). This Zenodo mirror provides direct, DOI-addressed URLs so the data can be fetched from any CI environment without credentials and without depending on consumer cloud storage. The signal data is unchanged — only filename conventions and archive layout have been normalized. License and attribution The original SPIE publication describes this dataset as “open access” and “publicly available” but does not declare an explicit Creative Commons license. This mirror is published under Zenodo’s other-open category on the same terms as the authors’ original distribution: open for research use with attribution to the paper (10.1117/12.2255697). If you are one of the dataset authors and wish to clarify the license or request removal of this mirror, please contact germanpressel@gmail.com (the corresponding author listed in the paper) or file an issue at NeuroTechX/moabb.

Re-hosted copy of the imagined-speech EEG database distributed by Pressel Coretto, Gareis, and Rufiner as a companion to DOI 10.1117/12.2255697 (SPIE / SIPAIM 2016). The authoritative upstream source is the authors' Google Drive file 0By7apHbIp8ENZVBLRFVlSFhzbHc, which is also what their institutional page at fich.unl.edu.ar/sinc/downloads/imagined_speech/ redirects to. The EEG signal data is bit-identical to that source; only filenames were normalized to a sub-NN convention (sub-01_eeg.mat was S01_EEG.mat) and the Base de Datos Habla Imaginada/ prefix was dropped for cleaner extraction. The authors' original Protocolo.txt (Spanish) and Registros_sujetos.xlsx are included unchanged. The authors' paper calls the dataset 'open access' but does not grant an explicit Creative Commons license. This mirror is provided under Zenodo's 'other-open' category on the same implicit terms: open for research with attribution to the paper. Takedown on author request. Authors of this dataset may contact germanpressel@gmail.com (corresponding author) or file an issue at https://github.com/NeuroTechX/moabb to clarify the license or request removal.