Electroencephalogram (EEG) is the electrical activity of the brain recorded by electrodes placed on the scalp. EEG signals are generally investigated for the diagnosis of mental conditions such as epilepsy, memory impairments, and sleep disorders. In recent years there has been another application using EEG: for brain-computer interface (BCI) designs (Vaughan & Wolpaw, 2006). EEG-based BCI desi...

This study reviews the originality and development of the Brain Computer Interface (BCI) system and focus on the BCI system design based on Blind Source Separation (BSS) techniques. The study also provides the recent trends and discusses some of a new ideas for BSS techniques in BCI architecture, articles which discussing the BCI system development were analysed, types of the BCI systems and th...

Recently, methodologies for developing brain-computer interface (BCI) games using the BCI have been actively researched. The existing general framework for processing brain waves does not provide the functions required to develop BCI games. Thus, developing BCI games is difficult and requires a large amount of time. Effective BCI game development requires a BCI game framework. Therefore the BCI...

Topological insulators (TIs) are an unusual phase of quantum matter with nontrivial spin-momentum-locked topological surface states (TSS). The electrical detection of spin-momentum-locking of TSS has been lacking till very recently. Many of the results are from samples with significant bulk conduction, such as Bi2Se3, where it can be challenging to separate the surface and bulk contribution to ...

Topological insulators (TIs) are an unusual phase of quantum matter with nontrivial spin-momentum locked topological surface states (TSS). The electrical detection of spin-momentum locking of the TSS in 3D TIs has been lacking till very recently. Many of the results are measured on samples with significant bulk conduction, such as metallic Bi2Se3, where it can be challenging to separate the sur...

Classifying different electroencephalogram (EEG) patterns is one of the key components to designing a usable Brain Computer Interface (BCI). Although it is well known that Support Vector Machine (SVM) is a strong classifier, it does not replace simple Linear Discriminant Analysis (LDA) or Nearest Neighbor Classifier (NNC), which are still in use in current BCI systems. This paper presents a com...

Developing neuroprostheses and advanced communication systems for patients with disabilities has involved considerable scientific and technological efforts. Many recent projects developed software and hardware based on BCIs for such patients. Principles of Brain Computer Interfaces (BCI), technologies used for this type of interfaces and the latest research activities in the field of BCIs are p...

Abstract Threshold properties and pulsed output of AlGaInP visible-emitting lasers with an asymmetric waveguide structure a bulk active layer are analysed. The effects the current leakage, increased by heating laser due to proximity electrical pulse source Joule in around this When optimising design, waveguiding shown be important, leading threshold currents decreasing, injection efficiency inc...

We report on the development and online testing of an electroencephalogram-based brain-computer interface (BCI) that aims to be usable by completely paralysed users-for whom visual or motor-system-based BCIs may not be suitable, and among whom reports of successful BCI use have so far been very rare. The current approach exploits covert shifts of attention to auditory stimuli in a dichotic-list...

A dedicated triple wavelength LED driver is presented for optical brain–computer interfacing (BCI). The solution caters for the constraints of a common-anode grounded case and modulation up to several kilohertz that allows source separation of light that has backscattered from the brain. With total harmonic distortion of 0.95% and a frequency range of 40 kHz, the driver has application in a con...