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

Volume

15

Issue

2

fYear

2007

fDate

6/1/2007 12:00:00 AM

Firstpage

322

Lastpage

324

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;

fLanguage

English

Journal_Title

Neural Systems and Rehabilitation Engineering, IEEE Transactions on

Publisher

ieee

ISSN

1534-4320

Type

jour

DOI

10.1109/TNSRE.2007.897032

Filename

4237170