Brain Training System Using Electroencephalography (EEG) for Neurorehabilitation of Hand Function After Stroke

Brain Training System Using Electroencephalography (EEG) for Neurorehabilitation of Hand Function After Stroke

In this project we will design a control algorithm to identify the focalized motor-related clusters for hand function on each stroke patient. A real-time feedback will control the robotic hand when motor imagery is successfully identified. Finally, the focalized BCI-robot training will be compared in a randomized controlled trial to evaluate the training effectiveness and changes in the EEG patterns.

Inclusion Criteria:

(1) sufficient cognition to follow simple instructions, as well as understand the content and purpose of the experiment (Mini-Mental State Examination (MMSE) score>25) ; (2) subcortical location of the ischemic lesion within the territory of the middle cerebral artery; (3) have moderate to severe motor disability at the paretic upper limb (assessed by Fugl-Meyer Assessment (FMA), Modified Ashworth Score of fingers (MAS), and Action Research Arm Test (ARAT))

Exclusion Criteria:

(1) severe hand spasticity, open hand wound or hand deformity; (2) visual field deficits; (3) aphasia, neglect, and apraxia.