Event-driven signal model and active recursive intent estimation for brain-computer interfaces
Brain-Computer Interface (BCI) systems can provide a new pathway of communication and control that can be used in both medical and non-medical domains. Electroencephalogram (EEG) signals have been shown to be effective in inferring user intent in BCI applications. However, in many cases, EEG-based c...
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| Online Access: | http://hdl.handle.net/2047/D20317887 |