Human Computer Confluence in BCI for Stroke Rehabilitation
This publication presents a novel device for BCI based stroke rehabilitation, using two feedback modalities: visually, via an avatar showing the desired movements in the user’s first perspective; and via electrical stimulation of the relevant muscles. Three different kinds of movements can be trained: wrist dorsiflexion, elbow flexion and knee extension. The patient has to imagine the selected motor movements. Feedback is presented online by the device if the BCI detects the correct imagination. Results of two patients are presented showing improvements in motor control for both of them.
KeywordsLinear Discriminant Analysis Motor Imagery Stroke Survivor Functional Electrical Stimulation Control Accuracy
This research has been partially supported by the European projects ComaWare (GA no. 650381), DeNeCor (ENIAC JU 2012 GA on. 324257) and CREAM (GA no. 265648).
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