DocumentCode :
747881
Title :
Linear and nonlinear methods for brain-computer interfaces
Author :
Müller, Klaus-Robert ; Anderson, Charles W. ; Birch, Gary E.
Author_Institution :
Fraunhofer FIRST.IDA, Berlin, Germany
Volume :
11
Issue :
2
fYear :
2003
fDate :
6/1/2003 12:00:00 AM
Firstpage :
165
Lastpage :
169
Abstract :
At the recent Second International Meeting on Brain-Computer Interfaces (BCIs) held in June 2002 in Rensselaerville, NY, a formal debate was held on the pros and cons of linear and nonlinear methods in BCI research. Specific examples applying EEG data sets to linear and nonlinear methods are given and an overview of the various pros and cons of each approach is summarized. Overall, it was agreed that simplicity is generally best and, therefore, the use of linear methods is recommended wherever possible. It was also agreed that nonlinear methods in some applications can provide better results, particularly with complex and/or other very large data sets.
Keywords :
electroencephalography; handicapped aids; learning automata; mathematical programming; reviews; EEG data sets; Fisher´s disciriminant; Second International Meeting on Brain-Computer Interfaces; feature spaces; linear methods; mathematical programming machines; nonlinear methods; support vector machines; Brain computer interfaces; Brain modeling; Computer science; Councils; Counting circuits; Electroencephalography; Feature extraction; Mathematical programming; Signal processing; Support vector machines; Algorithms; Brain; Electroencephalography; Humans; Linear Models; Models, Neurological; Neural Networks (Computer); Nonlinear Dynamics; 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.2003.814484
Filename :
1214711
Link To Document :
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