BNCI 2025-002 Continuous 2D Trajectory Decoding dataset
…4-class motor imagery dataset BNCI2014_004 : 2-class motor imagery dataset…
- Participants
- 10
- Channels
- 60 (10-05)
- Citations
- 20
- HED
- v8.4.0
- Size
- 7.38 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
100 results for "Motor imagery" · page 8 of 10 · ranked by relevance
…4-class motor imagery dataset BNCI2014_004 : 2-class motor imagery dataset…
THINGS-EEG2 is a large-scale EEG dataset comprising recordings from 10 subjects viewing 16,540 distinct training images and 200 test images presented via rapid serial visual presentation at 5 Hz. The dataset includes 63-channel EEG data sampled at 1000 Hz across 4 sessions per subject, with approximately 32,540 training trials and 16,000 test trials, designed to support computational modeling of human visual object recognition. Stimuli are drawn from the THINGS database, and the dataset includes resting-state recordings and behavioral annotations for each trial.
This dataset comprises preprocessed EEG recordings from 16 native French-speaking participants performing a forced picture naming task. Participants viewed images from the Snodgrass & Vanderwart corpus and were required to name them while EEG activity was recorded across baseline, visual stimulation, and naming phases. The dataset contains 270 trials per subject and was used to characterize spatiotemporal dynamics in EEG data using optical flow pattern analysis. Note: 16 participants represent the final cohort after 4 exclusions from an initial 20 subjects due to hardware failure.
Imported from OpenNeuro ds003801
…motor_imagery Imagery tasks: reach_forward, reach_backward, reach_left, reach_right…
…motor_imagery - **Imagery tasks**: left_hand_finger_tapping, right_hand_finger_tapping…
…motor_imagery Number of repetitions: 20 Data Structure -------------- Trials: {'per_session': 20…
This dataset comprises synchronized multimodal neurophysiological and biomechanical recordings from 128-channel EEG, electromyography (EMG), electrooculography (EOG), and motion capture during a perturbed beam-walking task. Participants performed four 10-minute sessions of standing or walking on a narrow balance beam while exposed to sensorimotor perturbations (visual field rotations or waist pulls). The dataset includes preprocessed EEG data with identified good channels and independent component analysis results, enabling investigation of cortical mechanisms underlying balance control and responses to perturbations.
NEMAR Dataset nm000106: handwriting - Handwriting movement detection from EMG
…self-initiated reach-and-grasp motor imagery tasks using three different recording…