Abstract. This paper addresses the problem of signal responses variability within a single subject in P300 speller Brain-Computer Interfaces. We propose here a method to cope with ...
Alain Rakotomamonjy, Vincent Guigue, G. Mallet, V....
Abstract. The P300 Speller has proven to be an effective paradigm for braincomputer interface (BCI) communication. Using this paradigm, studies have shown that a simple linear clas...
Most of the previous work on non-invasive brain-computer interfaces (BCIs) has been focused on feature extraction and classification algorithms to achieve high performance for the...
This paper presents a subject-independent EEG (Electroencephalogram) classification technique and its application to a P300-based word speller. Due to EEG variations across subje...
In this paper, we analyze the convergence of an iterative selftraining semi-supervised support vector machine (SVM) algorithm, which is designed for classi cation in small trainin...