Brain-computer interfaces (BCIs) based on motor imagery have been gaining attention as tools to facilitate recovery from movement disorders resulting from stroke or other causes. These BCIs can detect imagined movements that are typically required within conventional rehabilitation therapy. This information about the timing, intensity, and location of imagined movements can help assess compliance and control feedback mechanisms such as functional electrical stimulation (FES) and virtual avatars. Here, we review work from eight groups that each presented recent results with BCI-based rehabilitation at a workshop during the 6th International Brain-Computer Interface Meeting. We also present major directions and challenges for future research.
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