A multi-paradigm and longitudinal EEG dataset including the “sixth-finger” and “affected-hand” motor imagery of stroke patients
Motor imagery-based brain-computer interface (MI-BCI) applications in stroke rehabilitation aim to match brain activity with real-time feedback, thereby establishing closed-loop neural pathways and providing a basis for evaluating patients’ neuroplasticity changes. Thus, constructing EEG datasets under MI paradigms is...