Paper Info
Title
Local Neural Classifier for EEG-Based Recognition of Mental Tasks
Abstract
This paper proposes a new local neural classifier for the recognition of mental tasks from on-line spontaneous EEG signals. The classifier is embedded in a portable brain-computer interface called ABI, which has been evaluated with four young healthy persons. Subjects' performance is analyzed off-line and, for three of them on-line in the presence of biofeedback. The proposed ABI recognizes three mental tasks from on-line spontaneous EEG signals. Correct recognition is around 70%. This modest rate is largely compensated by two properties of ABI: wrong responses are below 5% and it makes decisions every 1/2 second. Also, since the subject and his/her personal ABI learn simultaneously from each other, subjects master it rapidly: one of the subjects achieved excellent control in just 5 days of training.
Year
Venue
Keywords
2000
IJCNN (3)
personal ABI,correct recognition,Local Neural Classifier,new local neural classifier,portable brain-computer interface,mental task,excellent control,subjects master,modest rate,EEG-Based Recognition,Mental Tasks,on-line spontaneous EEG signal,proposed ABI
DocType
ISBN
Citations 
Conference
0-7695-0619-4
2
PageRank 
References 
Authors
0.44
0
1
Name
Order
Citations
PageRank
Febo Cincotti119531.83