Stroke is a devastating neurological condition, often causing severe functional and cognitive deficits, sharply diminishing the patient’s quality of life. Among others, robot-assisted rehabilitation has been widely proposed to enhance the rehabilitation outcome. However, clinical scores and robotic parameters often used to inform rehabilitative-decision process are unfit to fully describe the neural reorganization that occur after a brain insult. The lack of reliable, simple, and sensitive neural biomarkers has potentially limited the clinical translation of these advanced rehabilitative technologies. Here, we show that EEG-topographic measures can be extracted as robust and sensitive biomarkers of stroke recovery to inform robotic therapies.
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