The experimental group showed considerable improvements in Fugl-Meyer Assessment scores compared with the control group, and the BCI system achieved satisfactory EEG classification accuracy (maximum 98.08%); increases in EEG accuracy, normalization of laterality coefficients and reinforcement of task-specific brain connectivity were observed after prolonged training. The authors say the hybrid system shows promise for neurorehabilitation. PMID 42044749, DOI 10.1016/j.jneumeth.2026.110780
Feasibility of a Hybrid SSVEP-Motor Imagery BCI with Robotic Feedback for Stroke Upper Limb Rehabilitation
Summary
Researchers assessed the feasibility of a hybrid brain-computer interface that integrates motor imagery (MI) and steady-state visual evoked potentials (SSVEP) with robotic glove feedback for upper limb motor rehabilitation in 32 stroke patients, split into a conventional-treatment control group and an experimental group receiving 10- or 20-day BCI interventions. The experimental group showed considerable improvement in Fugl-Meyer scores over the control group, and the BCI achieved EEG classification accuracy up to 98.08% with stable operation; after longer training, accuracy rose, the laterality coefficient moved toward normal, and task-related brain connectivity strengthened. The authors say the hybrid system may overcome the limits of conventional therapy and single-modality BCIs.
Why it matters
The study adds early evidence that combining two BCI modalities with robotic feedback can drive measurable Fugl-Meyer gains in stroke patients — an incremental but clinically concrete step beyond single-modality rehabilitation BCIs.
Compiled by BCIwiki from public sources
Sources · 1
pubmed.ncbi.nlm.nih.gov 2026-04-28
Chinese Academy of Medical Sciences & Peking Union Medical CollegeChina Rehabilitation Research CenterTianjin Medical UniversityNeurorehabilitationMovement DisordersChina