Related papers: Chromatic and High-frequency cVEP-based BCI Paradi…
Brain-computer interfaces (BCI) are promising communication devices between humans and machines. BCI based on non-invasive neuroimaging techniques such as electroencephalography (EEG) have many applications , however the dissemination of…
Color intensity projections (CIP) have been shown to improve the visualisation of greyscale angiography images by combining greyscale images into a single color image. A key property of the combined CIP image is the encoding of the arrival…
Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices. This review highlights the core decoding algorithms that enable multimodal BCIs, including a dissection of the elements, a unified view of…
Brain-computer interfaces (BCIs) often suffer from limited robustness and poor long-term adaptability. Model performance rapidly degrades when user attention fluctuates, brain states shift over time, or irregular artifacts appear during…
Families of cosmic inflation models predict a primordial gravitational-wave background that imprints B-mode polarization pattern in the Cosmic Microwave Background (CMB). High sensitivity instruments with wide frequency coverage and…
In this paper we will describe all necessary parts of Brain-Computer Interface (BCI), such as source of signals, hardware, software, analysis, architectures of complete system. We also will go along various applications of BCI, view some…
Brain-computer interfaces (BCIs) can provide an alternative means of communication for individuals with severe neuromuscular limitations. The P300-based BCI speller relies on eliciting and detecting transient event-related potentials (ERPs)…
Motor brain-computer interface (BCI) development relies critically on neural time series decoding algorithms. Recent advances in deep learning architectures allow for automatic feature selection to approximate higher-order dependencies in…
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have shown its robustness in facilitating high-efficiency communication. State-of-the-art training-based SSVEP decoding methods such as extended Canonical…
Over the last half century, the main application of Brain Computer Interfaces, BCIs has been controlling wheelchairs and neural prostheses or generating text or commands for people with restricted mobility. There has been very limited…
Brain-computer interfaces (BCIs) read neural signals directly from the brain to infer motor planning and execution. However, the implementation of this technology has been largely limited to laboratory settings, with few real-world…
In perceptual image coding applications, the main objective is to decrease, as much as possible, Bits Per Pixel (BPP) while avoiding noticeable distortions in the reconstructed image. In this paper, we propose a novel perceptual image…
Brain-computer interfaces (BCIs) promise to extend human movement capabilities by enabling direct neural control of supernumerary effectors, yet integrating augmented commands with multiple degrees of freedom without disrupting natural…
With the sensor scaling of next-generation Brain-Machine Interface (BMI) systems, the massive A/D conversion and analog multiplexing at the neural frontend poses a challenge in terms of power and data rates for wireless and implantable…
Lucid dreaming (LD) is a phenomenon during which the person is aware that he/she dreaming and is able to control the dream content. Studies have shown that only 20% of people can experience lucid dreams on a regular basis. However, LD…
Reliable control in motor imagery brain-computer interfaces (MI-BCIs) requires the precise decoding of user-specific neural rhythms, which vary significantly across individuals. The Common Spatial Pattern (CSP) algorithm is a cornerstone of…
We propose a fusion approach that combines features from simultaneously recorded electroencephalographic (EEG) and magnetoencephalographic (MEG) signals to improve classification performances in motor imagery-based brain-computer interfaces…
This study introduces a pioneering approach in brain-computer interface (BCI) technology, featuring our novel concept of complex visual imagery for non-invasive electroencephalography (EEG)-based communication. Complex visual imagery, as…
A new approach for implementing number of expressions, emotions and, actions to operate objects through the thoughts of brain using a Non-Invasive Brain Computing Interface (BCI) technique has been proposed. In this paper a survey on brain…
Current treatments for paraplegia induced by spinal cord injury (SCI) are often limited by the severity of the injury. The accompanying loss of sensory and motor functions often results in reliance on wheelchairs, which in turn causes…