nm000173
Motor Imagery ataset from Ofner et al 2017
EEG
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