Imagined Emotion Study
…states during acquisition of high-density EEG data. During the study, participants…
- Participants
- 34
- Channels
- 224 (biosemi)
- Citations
- 138
- Size
- 36.0 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
100 results for "high-density EEG" · page 5 of 10 · ranked by relevance
…states during acquisition of high-density EEG data. During the study, participants…
…Raw data are stored in BrainVision format (triplet of `*.eeg`, `*.vhdr`, `*.vmrk…
BigP3BCI Study J is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 character grid speller task. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects across 20 studies. The data were acquired at 256 Hz using 16-channel EEG with a g.USBamp amplifier and include target and non-target event classifications suitable for machine learning applications.
…The study was designed to investigate EEG correlates of cognitive activity during…
Imported from OpenNeuro ds007175
…dataset combining human-participant high-density electroencephalography (EEG) with physiological and continuous…
This dataset comprises EEG recordings from 54 healthy participants performing a P300-based brain-computer interface speller task, designed to investigate BCI illiteracy. The study includes 62 EEG channels and 4 EMG channels sampled at 1000 Hz, with participants completing offline training and online test phases using a 36-symbol row-column speller paradigm. The dataset achieved 96.7% accuracy with an 11.1% BCI illiteracy rate, providing a comprehensive resource for evaluating P300-based BCI performance and individual differences in BCI competence.
…60.0 Hz Online filters: {'highpass': 0.016, 'lowpass': 1000} Participants ------------ Number…
BigP3BCI Study O is a P300-based brain-computer interface dataset comprising EEG recordings from 18 ALS subjects across 2 sessions each, using a 9x8 character grid with supervised and checkerboard stimulus paradigms. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 electrode montage, designed for machine learning applications in BCI speller systems. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with recordings from approximately 267 subjects across 20 studies.
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on007420-blue…