…development of EEG-based emotion recognition algorithms for real-world applications. ## Overview…
EEG recordings from 15 healthy participants performing a P300-based brain-computer interface task for controlling a home appliance, specifically a door lock. Data were acquired with 31 active EEG channels at 500 Hz during a four-class visual oddball paradigm presented on an LCD display, with target and non-target flashes. Each subject completed 50 training and 30 testing blocks, including online testing with visual feedback.
…The dataset contains 5,184 trials collected during a visual object recognition…
EEG dataset from a masked-priming-style ERP study examining neural associations between fingerspelling, printed English words, and American Sign Language signs in deaf readers. Participants viewed 300 prime-target pairs in which primes were English words, ASL signs, or fingerspelled words, followed by four-letter English word targets, while performing an animal-detection task. The data support investigation of cross-modal and cross-script priming effects in deaf readers.
…Real-time EEG-based emotion recognition for neurohumanities: Perspectives from principal component…
EEG recordings from healthy participants performing self-initiated palmar and lateral reach-and-grasp actions, acquired simultaneously across three recording systems: gel-based laboratory EEG, water-based mobile EEG, and dry-electrode mobile EEG. The dataset supports investigation of the feasibility of decoding natural reach-and-grasp movement-related cortical potentials across EEG acquisition modalities for brain-computer interface applications. It is distributed in BIDS format as part of the MOABB benchmark collection.
A multi-modal dataset of 32-channel dry-electrode EEG recorded together with Virtual Glove hand-kinematic tracking during motor imagery and motor execution of three right-hand movements (open/close, wrist rotation, finger tapping). Eleven healthy participants completed a rest, motor imagery, motor execution sequence with eight repetitions of the triplet. This BIDS re-release was produced via MOABB from the published MOVING dataset.
…for advancing cross-context emotion recognition and enhancing the real-world application…
Stereo-electroencephalography (SEEG) recordings from four adults with drug-resistant epilepsy performing force-matching tasks with a power grasp and a lateral pinch. Two participants also completed blocks in which they only imagined producing the force. Each block contained trials at three force targets (20, 30 and 40% of maximum voluntary contraction). Recordings were sampled at 2000 Hz and include the analog force signal, and were converted to BIDS from a Dryad deposit.
…on Computer Vision and Pattern Recognition (CVPR), 1–9. https://doi.org…