…75.8% - **Correct Recognition Rate**: 63.2 - **Error Recognition Rate**: 75.8…
This dataset contains simultaneous scalp and ear-EEG recordings from six healthy right-handed participants performing cued left- and right-hand fist clenching (motor execution). It comprises 1114 trials recorded at 1000 Hz with a Neuroscan SynAmps2 amplifier. The data support evaluation of in-ear sensing for motor task classification and brain-computer interface research. This BIDS version was generated with MOABB from the original Zenodo deposit.
[ from 31 healthy participants, recorded with a 64-channel Neuroscan system at 1000 Hz across up to three sessions of 40 trials each. It is a derivative of the multi-paradigm Eye-BCI dataset, which combines EEG, eye-tracking and high-speed video for ocular activity analysis. It is provided through MOABB for benchmarking motor-related brain-computer interface decoding.
…copy-spell 'PATTERN RECOGNITION MACHINE LEARNING' (36 characters). Each character received 5…
EEG recordings from 20 participants performing a novel finger motor imagery paradigm in which cues for individual fingers were presented in random and sequential order blocks. The order of blocks was counterbalanced across participants. Data were acquired with a 65-channel g.tec system at 512 Hz and organized in BIDS format.
[ dataset combining 157-channel EEG and full-body motion capture from 20 healthy adults performing a spatial heading-change task. Participants followed a moving sphere and returned to their initial heading either by physically rotating on the spot or by using a joystick with a 2D desktop display. The dataset supports investigation of human cortical dynamics during full-body rotation and is formatted according to BIDS.
A NEMAR re-host and EMG-BIDS conversion of the public Meta emg2pose benchmark, pairing 2 kHz, 16-channel wrist surface electromyography with hand pose labels from a 26-camera motion-capture system. The release spans 193 users, about 370 hours, 29 behavioral stages and roughly 80 million labeled frames. It supports research on estimating hand pose from surface EMG.
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003421-blue…