Brain-Computer Interface (BCI) systems use brain activity as an input signal and enable communication without requiring bodily movement. This novel technology may help impaired patients users with disabilities to communicate their environment. Over the years, researchers investigated performance of subjects in different BCI paradigms, stating that 15%-30% are unable reach proficiency using a system therefore were labelled illiterates. Recent progress BCIs based on visually evoked potentials...

Brain-Computer Interfaces (BCIs) based on Steady-State Visually Evoked Potentials (SSVEPs) can be used as hand-free control device. To utilize this method in a real life scenario, we created system which smart home is controlled by BCI. Six devices the environment could with BCI system: The entrance door, wardrobe, kitchens' worktop and drawers, light of all rooms guide light. In presented paper, visual stimuli for were placed at multiple screens (placed different locations such kitchen...

Abstract Keyboards and smartphones allow users to express their thoughts freely via manual control. Hands-free communication can be realized with brain–computer interfaces (BCIs) based on code-modulated visual evoked potentials (c-VEPs). Various variations of such spellers have been developed: Low-target systems, multi-target systems dictionary support. In general, it is not clear which kinds are optimal in terms reliability, speed, cognitive load, load. The presented study investigates the...

Brain-computer interfaces (BCIs) measure brain activity and translate it to control computer programs or external devices. However, the generated by BCI makes measurements for objective fatigue evaluation very difficult, situation is further complicated due different movement artefacts. The performance could be increased if an online method existed objectively accurately. While BCI-users are moving, a novel automatic artefact removal technique used filter out these effects of this on mainly...

Responsive EEG-based communication systems have been implemented with brain-computer interfaces (BCIs) based on code-modulated visual evoked potentials (c-VEPs). The BCI targets are typically encoded binary m -sequences because of their autocorrelation property; the digits one and zero correspond to different target colours (usually black white), which updated every frame according code. While flickering patterns enable high speeds, they perceived as annoying by many users. Quintary (base 5)...

Brain-Computer Interfaces (BCIs) allow communication and control of the environment without use peripheral muscles. One standard BCI paradigms is based on steady state visual evoked potentials (SSVEPs), brain signals induced by gazing at a constantly flickering target. In this article, VR SSVEP-based steering simulation presented evaluated in comparison to desktop version. Three classes were used application. The experimental task was steer virtual vacuum robot collect 10 dust piles (for...

Brain-Computer Interface (BCI) provides a non-muscular communication by using the brain signals. During last decades, BCI-systems provided various graphical user interfaces, especially speller interfaces. Efforts had been made to increase speed and friendliness of system. In this paper, we are introducing browser-driven SSVEP-based BCI web (accessible at: https://bci-lab.hochschule-rhein-waal.de/en/speller/). This can be used with help major existing browsers. Thus, all international...

Brain-Computer Interface (BCI) interprets brain signals, which are measured by an electroencephalogram (EEG), allowing people to communicate without the need for any muscular movement. One of most commonly discussed applications in literature is BCI speller as a communication modality with disabilities. In Brain-Neural Computer (BNCI) other biosignals merged signals combine advantages both. Consequently, here-studied hybrid system discusses parallel usage Steady-State Visual Evoked Potential...

In this paper we examined different ways to inform the user of classification progress in our online SSVEPbased BCI speller. Different feedback was given based on distance from threshold, separately calculated for each stimulus. We focused comparison accuracies and spelling times associated with type. tested eight methods, one without comparison, two paradigms (an increase a decrease), three varying parameters, during an task. The eighth method combination best performing modalities. A 28...

In this paper we compared different visual feedback methods, informing users about classification progress in a steady-state evoked potential (SSVEP)-based brain-computer interface (BCI) speller application. According to results from our previous studies, changes stimulus size and contrast as online of have great impact on BCI performance SSVEP-based spellers. experiment further investigated these effects, tested 4-target SSVEP with much higher number subjects. Five scenarios were used...

Brain-computer interfaces (BCIs) based on code-modulated potentials (cVEPs) identify a target usually in the synchronous way (i.e. after preset time period system will produce command output). Hence, users have only limited amount of to fixate desired target. For practical usability BCI spellers it is important distinguish between intentional and unintentional fixations. In this paper we propose use threshold-based identification methods for cVEP paradigm. These were tested with dictionary...

Brain-Computer Interfaces (BCIs) allow users to communicate and control their environment without the use of peripheral muscles. One commonly used BCI paradigms is called steady state visual evoked potentials (SSVEPs). It controlled by brain signals induced through gazing at a constantly flickering light source. In this article, VR-based SSVEP-controlled simulation presented evaluated, in comparison standard desktopbased version. Three classes were application. The experimental task was...

Brain-computer interfaces (BCIs) based on code-modulated visual evoked potentials (c-VEPs) hold promise to serve as a fast and reliable hands-free communication tool for people with severe disabilities. A c-VEP BCI application presents flickering target objects (e. g. letters of keyboard) coded different time-lags code pattern. Template matching methods are used identify the interest. Unfortunately, this approach requires training session, in which several trials EEG data recorded analysed....

Steady-State Visually Evoked Potential (SSVEP) is widely used in Brain-Computer Interface (BCI) systems. However, the use of flickering stimuli at low frequencies causes visual fatigue for users. The increases when multiple are used, different frequencies. To overcome this problem, paper present a solution by using single high frequency (30 Hz) stimulus interface with 30 targets. In proposed system, initial recognition target was achieved through eye gaze position an eye-tracker, and...

In this paper the influence of different backgrounds was investigated on SSVEP-based BCI performance, with a focus measuring objective user fatigue. We tested three backgrounds: black screen, white noise, and video, spelling application (in which four distinct frequencies were used). measured information transfer rate (ITR), accuracy, several parameters could indicate fatigue levels. The data recorded EEG. level comfort before after experiment, as well subjective assessed using...

In this paper, the performance of a steady-state visually evoked potential (SSVEP)-based brain-computer interface (BCI) was evaluated after reducing number electroencephalography (EEG) electrodes used for recording. Our aim comparison using different electrodes, as well determining best electrode locations. The main benefit most efficient sites can be shortening preparation time needed setup BCI system. measured with EEG reduced from initially sixteen to six intermediate step, and finally...

Brain-Computer Interfaces (BCIs) based on code-modulated visual evoked potentials can be used as hand-free communication tool for severely disabled people. In this paper we propose a filter bank design c-VEP BCIs alpha, beta and gamma sub-bands. The approach was tested using dictionary driven spelling application utilizing flexible time-windows. graphical user interface offers word suggestions that are updated after each selection. system with 18 healthy participants. Performance of sentence...

Many individuals require Aided Augmentative and Alternative Communication (AAAC) to communicate, especially when traditional AAC, like sign language, is not an option due some movement impairments. This paper presents a high tech AAAC using Surface Electromyography (sEMG) signals as input modality for the direct control of speller presented on Graphical User Interface (GUI). The GUI displays alphabetical letters, special characters, delete option. aim this study introduce examine performance...

Event-Related Potential (ERP) is one of the brain signal features which are used in Electroencephalography (EEG) based research and application development, such as Brain-Computer Interface (BCI) applications. Recently, single-trial ERP has been main interests researchers field BCI neuroscience. In this paper, an offline study evaluated feasibility developing online guessing game, on ERP, was presented. The objective to determine optimal methods parameters needed achieve high classification...