Robotic Grasping and Placement Controlled by EEG-Based Hybrid Visual and Motor Imagery
Paper • 2603.03181 • Published
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EEG-Graspbot Dataset
This dataset contains the offline EEG data for EEG-Graspbot.
The dataset includes five anonymized participants, labeled from sub00 to
sub04. Each participant has two task types:
VI: visual imageryMI: motor imagery
Data Organization
raw-data/: anonymized raw EEG BDF files and behavioral CSV files.prep-data/: preprocessed EEG FIF files generated from the raw BDF files.
Preprocessing
The preprocessed files in prep-data/ were generated with a 0.5-100 Hz
band-pass filter, 50 Hz notch filtering, rereferencing, EOG channel
construction, ICA-based artifact correction with 20 ICA components, and
resampling to 100 Hz.
Links
- Project page: https://yichangliu1224.github.io/EEG-Graspbot/
- Paper page: https://arxiv.org/abs/2603.03181
- GitHub page: yichangliu1224/EEG-Graspbot
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