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Local Neural Classifier for EEG-Based Recognition of Mental Tasks
Como, Italy July 24-July 27
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.10004IEEE-INNS-ENNS International Joint Co ...
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José del R. Millán, ISIS, Joint Research Centre, European Commission
Josep Mouriño, ISIS, Joint Research Centre, European Commission
Fabio Babiloni, Università Rome & La Sapienza and Helsinki University of Technology
Febo Cincotti, IRCCS S. Lucia
Markus Varsta, Helsinki University of Technology
Jukka Heikkonen, Helsinki University of Technology
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.
Citation:
José del R. Millán, Josep Mouriño, Fabio Babiloni, Febo Cincotti, Markus Varsta, Jukka Heikkonen, "Local Neural Classifier for EEG-Based Recognition of Mental Tasks," ijcnn, vol. 3, pp.3632, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3, 2000
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