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 [BibTeX] [Marc21]
On the Need for On-Line Learning in Brain-Computer Interfaces
Type of publication: Conference paper
Citation: millan:2004:ijcnn
Booktitle: Proceedings of the International Joint Conference on Neural Networks
Year: 2004
Month: 7
Address: Budapest, Hungary
Note: IDIAP-RR 03-30
Crossref: rr03-30:
Abstract: In this paper we motivate the need for on-line learning in brain-computer interfaces (BCI) and illustrate its benefits with the simplest method, namely fixed learning rates. However, the use of this method is supported by the risk of hampering the user to acquire suitable control of the BCI if the embedded classifier changes too rapidly. We report the results with 3 beginner subjects in a series of consecutive recordings, where the classifiers are iteratively trained with the data of a given session and tested on the next session. Interestingly, performance improved over sessions significantly for 2 of the subjects. These results show that on-line learning improves systematically the performance of the subjects. Moreover, performance with on-line learning is statistically similar to that obtained training the classifier off-line with the same amount of data.
Userfields: ipdmembership={learning},
Projects Idiap
Authors Millán, José del R.
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Total mark: 0
  • millan_2004_ijcnn.pdf