Multimodal upper-limb MI/ME EEG (Jeong et al. 2020)
A multimodal EEG dataset comprising motor imagery and motor execution data from 25 healthy subjects performing 11 intuitive upper-limb movement tasks (6 reaching, 3 grasping, 2 wrist twisting) across 3 sessions. The dataset includes 71-channel EEG recordings (60 EEG, 4 EOG, 7 EMG channels) sampled at 1000 Hz with synchronized behavioral annotations, designed for brain-computer interface research and motor control applications. This is a BIDS-formatted derivative dataset converted from the original Jeong et al. 2020 publication using MOABB (Mother of All BCI Benchmarks).
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Coming soon. Per-file data-quality summaries are precomputed by the NEMAR processing pipeline. The static aggregate is on the way — tracked at nemar-cli#511.