One of the key issues in the development of braincomputer interfaces (BCIs) is the improvement of their current information transfer rate. In order to achieve that objective at least two aspects of BCI design should be considered: classification accuracy and protocol specification. In this paper we show how combination of classifiers using fuzzy measures and the Choquet integral can be applied to the context of EEG-based BCI and study whether its use, together with an appropriate application protocol, can lead to an increase in the information transfer rate.
Cavrini, F., Bianchi, L., Quitadamo, L., Abbafati, M., Saggio, G. (2011). Use of the Choquet Integral for Combination of Classifiers in P300 Based Brain-Computer Interface. In Medical Measurements and Applications Proceedings (MeMeA), 2011 IEEE International Workshop on. Bari : IEEE [10.1109/MeMeA.2011.5966688].
Use of the Choquet Integral for Combination of Classifiers in P300 Based Brain-Computer Interface
BIANCHI, LUIGI;SAGGIO, GIOVANNI
2011-05-31
Abstract
One of the key issues in the development of braincomputer interfaces (BCIs) is the improvement of their current information transfer rate. In order to achieve that objective at least two aspects of BCI design should be considered: classification accuracy and protocol specification. In this paper we show how combination of classifiers using fuzzy measures and the Choquet integral can be applied to the context of EEG-based BCI and study whether its use, together with an appropriate application protocol, can lead to an increase in the information transfer rate.| File | Dimensione | Formato | |
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Use of the Choquet Integral for Combination of Classifiers in P300 Based BCI.pdf
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