Brain-computer interface (BCI) translates users’ brain activities into commands to control assistive devices. Notwithstanding the tremendous advances that have been made, current BCI algorithms for neuroprosthetics control still need to be further improved. In this thesis, I demonstrate that the hybrid BCI, by exploiting electroencephalography (EEG) signals alongside other biosignals, represents an intriguing technology for feed-forward control, sensory substitution, as well as for the quantification of the brain's perception of external sensory stimuli.
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Brain-computer interface (BCI) translates users’ brain activities into commands to control assistive devices. Notwithstanding the tremendous advances that have been made, current BCI algorithms for neuroprosthetics control still need to be further improved. In this thesis, I demonstrate that the hybrid BCI, by exploiting electroencephalography (EEG) signals alongside other biosignals, represents an intriguing technology for feed-forward control, sensory substitution, as well as for the quantific...
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