Title :
Studying the Use of Fuzzy Inference Systems for Motor Imagery Classification
Author :
Fabien, Lotte ; Anatole, Lécuyer ; Fabrice, Lamarche ; Bruno, Arnaldi
Author_Institution :
IRISA Rennes, Rennes
fDate :
6/1/2007 12:00:00 AM
Abstract :
This paper studies the use of fuzzy inference systems (FIS) for motor imagery classification in electroencephalography (EEG)-based brain-computer interfaces (BCI). 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.
Keywords :
electroencephalography; fuzzy reasoning; human computer interaction; medical signal processing; neurophysiology; signal classification; user interfaces; EEG-based brain-computer interfaces; data analysis; electroencephalography; fuzzy inference systems; motor imagery classification; Brain–computer interface (BCI); classification; electroencephalography (EEG); fuzzy inference system; motor imagery; Algorithms; Brain; Electroencephalography; Evoked Potentials, Motor; Fuzzy Logic; Humans; Imagination; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; User-Computer Interface;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2007.897032
