Most existing brain-computer interfaces (BCIs) detect specific mental activity in a so-called synchronous paradigm. Unlike synchronous systems which are operational at specific system-defined periods, self-paced (asynchronous) interfaces have the advantage of being operational at all times. The low-frequency asynchronous switch design (LF-ASD) is a 2-state self-paced BCI that detects the presen...

Brain-Computer Interfaces (BCI) are communication systems that enable subjects to send commands to computers by using only their brain activity [1]. Most existing BCI are based on ElectroEncephaloGraphy (EEG) as the measure of brain activity [1]. So far, BCI have been proven to be very promising communication and control tools for disabled people [1]. A promising brain signals used in the desig...

A large number of incommensurable metrics are currently used to report the performance of brain-computer interfaces (BCI) used for augmentative and alterative communication (AAC). The lack of standard metrics precludes the comparison of different BCI-based AAC systems, hindering rapid growth and development of this technology. This paper presents a review of the metrics that have been used to r...

This article evaluates two ways of characterization of EEG signals for classification of activity and linguistic inactivity, essential preprocess for the development of brain-computer interfaces (BCI) based on imagined speech. The first characterization used the calculation of the teager energy based on the discrete wavelet transform (DWT). The second characterization was based on the calculati...

EEG-based Brain-computer interfaces (BCI) are facing basic challenges in real-world applications. The technical difficulties in developing truly wearable BCI systems that are capable of making reliable real-time prediction of users' cognitive states in dynamic real-life situations may seem almost insurmountable at times. Fortunately, recent advances in miniature sensors, wireless communication ...

Brain-computer interfaces (BCIs), invasive or non-invasive, have projected unparalleled vision and promise for assisting patients in need to better their interaction with the surroundings. Inspired by BCI-based rehabilitation technologies nerve-system impairments amputation, we propose an electromagnetic brain-computer-metasurface (EBCM) paradigm, regulated human's cognition brain signals direc...

We combined the new developments of multimodal Brain-Computer Interfaces (BCI) and wireless EEG headsets with art by creating BrainBrush. Users can paint on a virtual canvas by moving their heads, blinking their eyes and performing selections using a P300 BCI. A qualitative evaluation (n=13) was done. A questionnaire was administered and structured interviews were conducted to assess the usabil...

Brain Computer Interface (BCI) is an alternative communication system which allows users to send commands and/or messages toward the outside not crossing the normal output channels of the brain, but conveying these outputs from the human brain to a computer (Wolpaw et al., 2002). In an EEG-based BCI messages are obtained from brain activity. This study presents a novel P300 based Brain Computer...

The challenges of research into brain-computer interfaces (BCI) include significant individual differences in learning pace and in the effective operation of BCI devices. The use of neurofeedback training is a popular method of improving the effectiveness BCI operation. The purpose of the present study was to determine to what extent it is possible to improve the effectiveness of operation of s...

INTRODUCTION Brain-computer interfaces (BCIs), or brain-machine interfaces (BMIs) involve real-time direct connections between the brain and a computer (Kubler, 2009; Wolpaw and Wolpaw, 2011). Bidirectional feedback between the user and the system produces physical changes that can restore some degree of motor or communicative control for individuals with lost limbs, extensive paralysis or who ...