Most of the previous work on brain-computer interfaces (BCIs) exploiting the P300 in electroencephalography (EEG) has focused on low-level signal processing algorithms such as feature extraction and classification methods. Although a significant improvement has been made in the past, the accuracy of detecting P300 is limited by the inherently low signal-to-noise ratio in EEGs. In this paper, we...

Brain-computer interfaces (BCI) enable non-muscular powerful channel for communicating thanks to direct communication between the user’s brain and a computer. In this article, the presented BCI concerns the P300 speller which enables people to write a text on a computer by estimating P300 evoked potentials. In this work, an unsupervised algorithm is introduced for signal subspace estimation: th...

In this paper, we propose a classification algorithm for P300-based Brain Computer Interface (BCI). Brain Computer Interface (BCI) with P300 speller helps Amyotrophic Lateral Sclerosis (ALS) patients to spell words with the help of their brain signal activities. Amyotrophic Lateral Sclerosis (ALS) also known as Lou Gehrig's disease in which certain nerve cells in brain and spinal cord also call...

This study provides a comprehensive test of the head–related impulse response (HRIR) to an auditory spatial speller brain–computer interface (BCI) paradigm, including a comparison with a conventional virtual headphone–based spatial auditory modality. Five BCI–naive users participated in an experiment based on five Japanese vowels. The auditory evoked potentials obtained produced encouragingly g...

We consider an EEG-based, wireless braincomputer interface (BCI) with which subjects can “mind spell” text on a computer screen. The application is based on the detection of the P300 event-related potential (ERP). The frequency range for preprocessing the EEG recordings, and the location and length of the time interval after stimulus onset, are selected with respect to the classification accura...

This study reports on a head related impulse response (HRIR) application to an auditory spatial brain-computer interface (BCI) speller paradigm. Six experienced and five BCInaive users participated in an experimental spelling set up based on five Japanese vowels. Obtained auditory evoked potentials resulted with encouragingly good and stable P300-responses in online BCI experiments. Our case st...

OBJECTIVE In this work we propose a probabilistic graphical model framework that uses language priors at the level of words as a mechanism to increase the performance of P300-based spellers. APPROACH This paper is concerned with brain-computer interfaces based on P300 spellers. Motivated by P300 spelling scenarios involving communication based on a limited vocabulary, we propose a probabilist...