Title :
Pattern Recognition of EEG Signals During Motor Imagery
Author :
Nagata, Koichi ; Mihara, Makoto ; Yamagutchi, Tomonari ; Taniguchi, Masaaki ; Inoue, Katsuhiro ; Pfurtscheller, Gert ; Kumamaru, Kousuke
Author_Institution :
Dept. of Syst. Innovation & Informatics, Kyushu Inst. of Technol., Fukuoka
Abstract :
Electroencephalograph (EEG) recordings during the right and the left hand motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by e.g., handicap users with amyotrophic lateral sclerosis (ALS). The conventional method purposes the recognition of the right hand and the left hand motor imagery. In this study, statistical pattern recognition method based on AR model is introduced to discriminate the EEG signals recorded during the right hand, the left hand and the right foot motor imagery. And the recognition of the hand motor imagery and the foot motor imagery also is carried out. Finally, the effectiveness of our method is confirmed through the experimental studies
Keywords :
electroencephalography; human computer interaction; medical signal processing; pattern recognition; signal classification; EEG signals; amyotrophic lateral sclerosis; brain-computer interface; communication channel; computer screen cursor; electroencephalograph; foot motor imagery; hand motor imagery; handicap users; statistical pattern recognition; Biomedical engineering; Biomedical informatics; Brain computer interfaces; Brain modeling; Electroencephalography; Feedback; Foot; Image recognition; Monitoring; Pattern recognition; AR-model; EEG; brain computer interface; motor imagery;
Conference_Titel :
SICE-ICASE, 2006. International Joint Conference
Conference_Location :
Busan
Print_ISBN :
89-950038-4-7
Electronic_ISBN :
89-950038-5-5
DOI :
10.1109/SICE.2006.315676
