Journal
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
Volume 15, Issue 2, Pages 322-324Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSRE.2007.897032
Keywords
brain-computer interface (BCI); classification; electroencephalography (EEG); fuzzy inference system; motor imagery
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This paper studies the use of fuzzy inference systems (FISs) for motor imagery classification in electroencephalography (EEG)-based brain-computer interfaces (BCIs). The results of the four studies achieved are promising as, on the analysed data, the used FIS was efficient, interpretable, showed good capabilities of rejecting outliers and offered the possibility of using a priori knowledge.
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