Related Experiment Video
Updated: Sep 23, 2026
Motor Imagery Brain-Computer Interface in Rehabilitation of Upper Limb Motor Dysfunction After Stroke
Published on: September 1, 2023
Neurofeedback-Guided Motor Imagery in Chronic Stroke: A Case Series on Upper-Limb Recovery, Cortical Activation, and
Raquel Carvalho1,2, Elsa Azevedo3,4, Paulo Marques5,6
1Rise-Health -Escola Superior de Tecnologias da Saúde de Tâmega E Sousa, Paredes, Portugal. raquel.carvalho@ipsn.cespu.pt.
Background:
Brain-computer interface (BCI) systems combined with motor imagery (MI) have emerged as promising tools in neurorehabilitation. Real-time neurofeedback may further enhance motor recovery by promoting use-dependent neuroplasticity; however, evidence in chronic stroke remains limited, particularly from controlled pilot studies.
Objective:
This case series explored the feasibility and preliminary effects of EEG-based BCI neurofeedback combined with MI and physiotherapy on upper-limb motor function and brain activation patterns in individuals with chronic stroke.
Methods:
In a double-blind, controlled protocol, seven individuals with chronic stroke were allocated to either an experimental group receiving MI with real-time EEG-based BCI neurofeedback or a control group receiving MI with sham feedback. All participants completed a standardized four-week physiotherapy program. Motor outcomes were assessed with the Action Research Arm Test, Fugl-Meyer Assessment, Motor Assessment Scale, and grip strength, with functional changes interpreted against minimal clinically important difference (MCID) thresholds. Neuroplastic changes were explored using EEG-derived symmetry measures and task-related functional MRI.
Results:
Participants receiving real neurofeedback exhibited consistent improvements exceeding MCID thresholds in at least one functional outcome, most notably grip strength. This group also demonstrated more symmetrical EEG activity and more consistent sensorimotor and cerebellar activation patterns on fMRI. In contrast, responses in the sham group were more variable and appeared influenced by a single high responder.
Conclusions:
These findings support the feasibility of integrating EEG-based BCI neurofeedback with MI and physiotherapy in chronic stroke rehabilitation. The observed functional gains and associated neurophysiological changes suggest a preliminary, exploratory role for this intervention in promoting upper-limb recovery in this small sample.
