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Motor Imagery ataset from Ofner et al 2017

This dataset comprises EEG recordings from 15 healthy subjects performing six different upper limb movements (elbow flexion/extension, forearm supination/pronation, hand open/close) and rest conditions in both movement execution and motor imagery modalities. The study investigates neural encoding of individual upper limb movements using low-frequency EEG signals (0.3-3 Hz) and achieves classification accuracies of 55-87% for executed movements and 27-73% for imagined movements. Source localization analysis identifies discriminative movement information in premotor areas, primary motor cortex, somatosensory cortex, and posterior parietal cortex, with applications toward non-invasive control of motor neuroprostheses and robotic arms.

Participants: 15
Channels: 61 (10-05)
Citations: 94
HED: v8.4.0
Size: 34.0 GB
Version: v1.0.3
Updated: Aug 18, 2026

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