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Feedback error-related potentials are a promising brain process in the field of rehabilitation since they are related to human learning. Due to the fact that many therapeutic strategies rely on the presentation of feedback stimuli, potentials generated by these stimuli could be used to ameliorate the patient's progress. In this paper we propose a method that can identify, in real-time, feedback evoked...
Always, one of the issues in the brain-computer interface (BCI) is to extract components from raw EEG data that have more information in order to separate task-related potentials from other neural and artifactual EEG sources. In this paper, a new method is proposed for extracting components from raw EEG data such that these components have maximal information for separating task-related potentials...
Optimizing a classifier is a subject of great interest in the research area. A lot of methods inspired of biological metaphors are proposed for this task. This paper present a new algorithm based on the natural immune metaphors which select a proper subset of features and optimal parameters of a support vector machines (SVM) classifier. The designed optimization method is validated for ERP assessment...
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