Related papers: Motor Imagery Classification for Asynchronous EEG-…
Reliable brain-computer interface (BCI) control of robots provides an intuitive and accessible means of human-robot interaction, particularly valuable for individuals with motor impairments. However, existing BCI-Robot systems face major…
Brain computer interface (BCI) has been popular as a key approach to monitor our brains recent year. Mental states monitoring is one of the most important BCI applications and becomes increasingly accessible. However, the mental state…
Brain-computer interface (BCI) technology establishes a direct communication pathway between the brain and external devices. Current visual BCI systems suffer from insufficient information transfer rates (ITRs) for practical use. Spatial…
Motor imagery (MI) based EEG represents a frontier in enabling direct neural control of external devices and advancing neural rehabilitation. This study introduces a novel time embedding technique, termed traveling-wave based time…
EEG-based brain-computer interfaces (BCIs) have shown promise in various applications, such as motor imagery and cognitive state monitoring. However, decoding visual representations from EEG signals remains a significant challenge due to…
New trends on brain-computer interface (BCI) design are aiming to combine this technology with immersive virtual reality in order to provide a sense of realism to its users. In this study, we propose an experimental BCI to control an…
This paper presents a systematic literature review on Brain-Computer Interfaces (BCIs) in the context of Machine Learning. Our focus is on Electroencephalography (EEG) research, highlighting the latest trends as of 2023. The objective is to…
In recent years, the rapid development of neuroimaging technology has been providing many powerful tools for cognitive neuroscience research. Among them, the functional magnetic resonance imaging (fMRI), which has high spatial resolution,…
BCI systems are able to communicate directly between the brain and computer using neural activity measurements without the involvement of muscle movements. For BCI systems to be widely used by people with severe disabilities, long-term…
Brain-computer interface (BCI) is used for communication between humans and devices by recognizing status and intention of humans. Communication between humans and a drone using electroencephalogram (EEG) signals is one of the most…
A major objective of Brain-Computer interfaces (BCI) is to restore communication and control in patients with severe motor impairments, like people with Locked-in syndrome. These patients are left only with limited eye and eyelid movements.…
We present a framework that integrates EEG-based visual and motor imagery (VI/MI) with robotic control to enable real-time, intention-driven grasping and placement. Motivated by the promise of BCI-driven robotics to enhance human-robot…
Human-robot collaboration has the potential to maximize the efficiency of the operation of autonomous robots. Brain-machine interface (BMI) would be a desirable technology to collaborate with robots since the intention or state of users can…
The performance of brain-computer interfaces (BCIs) improves with the amount of available training data, the statistical distribution of this data, however, varies across subjects as well as across sessions within individual subjects,…
In this paper, we evaluate a semi-autonomous brain-computer interface (BCI) for manipulation tasks. In such system, the user controls a robotic arm through motor imagery commands. In traditional process-control BCI systems, the user has to…
Motor imagery (MI) classification based on electroencephalogram (EEG) is a widely-used technique in non-invasive brain-computer interface (BCI) systems. Since EEG recordings suffer from heterogeneity across subjects and labeled data…
Despite the general assumption that completely locked-in state (CLIS) patients remain conscious and aware of their environment, the effectiveness of brain-computer interfaces (BCIs) in facilitating communication has been limited, as…
One of the greatest goals of neuroscience in recent decades has been to rehabilitate individuals who no longer have a functional relationship between their mind and their body. Although neuroscience has produced technologies which allow the…
Brain-Computer Interface (BCI) uses brain signals in order to provide a new method for communication between human and outside world. Feature extraction, selection and classification are among the main matters of concerns in signal…
Objective: Motor Imagery (MI) serves as a crucial experimental paradigm within the realm of Brain Computer Interfaces (BCIs), aiming to decoding motor intentions from electroencephalogram (EEG) signals. Method: Drawing inspiration from…