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Updated: Apr 24, 2026
Efficiently Recording the Eye-Hand Coordination to Incoordination Spectrum
Published on: March 21, 2019
Intention-Action Conflict EEG-Hand Kinematics Dataset for Unimanual Control under Congruent and Incongruent
Mengpu Cai1,2, Rongrong Fu3,4, Yaodong Wang5
1School of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China.
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The Intention-Action Conflict EEG-Hand Kinematics Dataset (IACKD) is a joint resource for studying congruent and incongruent intention-action conditions during unimanual control. It comprises 7,040 trials from 15 participants. Each trial includes a 1-s pre-movement period and a movement-execution period. A target frame and a controllable ball define the task; ball color cues congruency (red = same direction; yellow = opposite). EEG was recorded with a 32-channel Compumedics Neuroscan system at 1024 Hz, and 3-D hand trajectories were captured with Leap Motion at 170 Hz. Streams are time-aligned, and complete preprocessing and alignment scripts are provided. Technical validation includes readiness potentials at C3/C4/Cz, μ/β-band ERD/ERS with post-movement β rebound, sub-30-ms cross-modal residuals on >99.375% of trials, and expected completion-time differences between congruent and incongruent conditions. IACKD is intended for reuse in intention decoding, continuous trajectory decoding, and evaluation of decoder robustness under conflict or perturbed feedback.
