The P300 response exhibits abnormalities in autism spectrum disorder (ASD) and can potentially be used as ASD biomarker. Machine learning approaches represent useful tools for processing EEG signals by associating a cognitive state to the input ...

Music has been used to express and communicate emotional states through its different dimensions such as tone, rhythm, melody, and harmony. Consonant harmonies consistently are rated as pleasant whereas dissonant are considered unpleasant. The ...

Brain-computer interfaces (BCIs) enable communication between the human brain and external devices. However, different factors such as subject specificity lead to excessive individual dependency on conventional BCI systems and deterioration of the ...

The Steady State Visual Evoked Potential (SSVEP) is a widely used component in BCIs due to its high noise resistance and low equipment requirements. Recently, a novel SSVEP-based paradigm has been introduced for direction detection, in which, ...

• SE-TRCA method is introduced for direction detection using SSVEP component analysis.
• SE-TRCA extracts both spatial and spectral features simultaneously.
• SE-TRCA achieves high performance in direction detection and frequency ...

Event-related potential signal classification is a really difficult challenge due to the low signal-to-noise ratio. Deep neural networks (DNN), which have been employed in different machine learning areas, are suitable for this type of ...

Brain–computer interface (BCI) provides a new communication pathway for severely disabled people and enables them to communicate with external world using only their brain activity. P300-based BCI speller helps patients spell words using their ...

Brain–computer interfaces can allow users to select letters or other targets on a computer screen without any muscular activity. One of the most popular EEG-based spelling systems is employed with P300 potentials, eliciting the brain's positive ...

To make the world more advanced we are trying to improve several things and one of them is the Internet of Things. The real-world object can be turned into an intelligent one by using this technology and nowadays it’s collaborating with many other ...

Brain-computer interfaces (BCIs) can help people with disabilities to communicate with others, express themselves, and even create art. In this paper, a BCI painting system using a hybrid control approach based on steady-state visual evoked ...

• We develop a BCI painting system using a SSVEP/P300-based hybrid control approach.
• Tool selection accuracy of our system is higher than P300 brain painting system.
• Information transfer rate of our system is higher than P300 brain ...

Creation of streaming video stimuli that allow for strict experimental control while providing ease of scene manipulation is difficult to achieve but desired by researchers seeking to approach ecological validity in contexts that involve ...

Reliable and accessible voting systems are essential for democratic societies as they are a vital link between the democratic representation and its citizens. The current voting systems need further accessibility features to aid people with ...

• First method based on deep learning that provides robust asynchronous control of ERP-based spellers through monitoring of user attention.

Background and Objective. Brain-computer interfaces (BCI) based on event-related potentials (ERP) are a promising technology for alternative and augmented communication in an assistive context. However, most approaches ...

The processing and classification of electroencephalographic signals (EEG) are increasingly performed using deep learning frameworks, such as convolutional neural networks (CNNs), to generate abstract features from brain data, automatically ...

• EEG-TCFNet is proposed for P300 BCI of smart home interaction in natural environments.
• An assessment of Fuzzy Neural Block (FNB) with different deep learning architectures.
• The study contains both healthy and patients (post-stroke) ...

Most of the current Brain–Computer Interfaces (BCIs) application scenarios use electroencephalographic signals (EEG) containing the subject’s information. It means that if EEG were maliciously manipulated, the proper functioning of BCI frameworks ...

Fatigue can lead to the decline of target recognition accuracy in small target detection task based on the rapid serial visual presentation (RSVP) paradigm. In this study, event-related potential (ERP) technique was used to study the P300 characteristics ...

Electroencephalography (EEG) signals elicited by multimodal stimuli can drive brain-computer interfaces (BCIs), and research has demonstrated that visual and auditory stimuli can be employed simultaneously to improve BCI performance. ...

• This study proposed a P300-based RSMP BCI that uses artificial face and voice stimuli.

Electroencephalogram (EEG) performed an increasingly important role in user experience research. The study applied P300, one of the main components of event-related potentials (ERPs), into the evaluation of digital dashboard layouts. The amplitude ...

This paper addresses the development of a dementia screening tool using a character-input-type brain–computer Interface (BCI). A blinking letter board is presented to the subject for each matrix by the character-input-type BCI, and by keeping an ...

Alzheimer's disease is a typical brain cognitive dysfunction disease that seriously affects the work and life of patients. How to diagnose this disease early has always been a concentration and it is also a meaningful field to study. Recently, novel ...

There is a significant progress in the development of brain-controlled mobile robots and robotic arms in the recent years. New advances in electroencephalography (EEG) technology have led to the possibility of controlling external devices, such as ...