Related papers: High Aptitude Motor Imagery BCI Users Have Better …
Present Brain-Computer Interfacing (BCI) technology allows inference and detection of cognitive and affective states, but fairly little has been done to study scenarios in which such information can facilitate new applications that rely on…
As the proliferation of technology dramatically infiltrates all aspects of modern life, in many ways the world is becoming so dynamic and complex that technological capabilities are overwhelming human capabilities to optimally interact with…
A brain-computer interface (BCI) is used not only to control external devices for healthy people but also to rehabilitate motor functions for motor-disabled patients. Decoding movement intention is one of the most significant aspects for…
Non-invasive steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) systems offer high bandwidth compared to other BCI types and require only minimal calibration and training. Virtual reality (VR) has been already…
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…
A calibration procedure is required in motor imagery-based brain-computer interface (MI-BCI) to tune the system for new users. This procedure is time-consuming and prevents na\"ive users from using the system immediately. Developing a…
This paper provides a proof of concept for an EEG-based reconstruction of a visual image which is on a user's mind. Our approach is based on the Rapid Serial Visual Presentation (RSVP) of polygon primitives and Brain-Computer Interface…
A brain-computer interface (BCI) establishes a direct communication pathway between the human brain and a computer. It has been widely used in medical diagnosis, rehabilitation, education, entertainment, etc. Most research so far focuses on…
Emerging evidence shows that the modular organization of the human brain allows for better and efficient cognitive performance. Many of these cognitive functions are very fast and occur in subsecond time scale such as the visual object…
Brain-Computer Interfaces (BCIs) based on Steady State Visually Evoked Potentials (SSVEPs) have proven effective and provide significant accuracy and information-transfer rates. This family of strategies, however, requires external devices…
The present paper examines the viability of a radically novel idea for brain-computer interface (BCI), which could lead to novel technological, experimental and clinical applications. BCIs are computer-based systems that enable either…
A brain-computer interface (BCI) based on electroencephalography (EEG) is a promising technology for enhancing virtual reality (VR) applications-in particular, for gaming. We focus on the so-called P300-BCI, a stable and accurate BCI…
In this paper we introduce the concept of Brain-Computer Interface (BCI) inhibitor, which is meant to standby the BCI until the user is ready, in order to improve the overall performance and usability of the system. BCI inhibitor can be…
Non-invasive electroencephalography (EEG)-based brain-computer interfaces (BCIs) offer an intuitive means for individuals with severe motor impairments to independently operate assistive robotic wheelchairs and navigate built environments.…
Humans activate muscles to shape the mechanical interaction with their environment, but can they harness this control mechanism to best sense the environment? We investigated how participants adapt their muscle activation to visual and…
This paper presents an accurate and robust embedded motor-imagery brain-computer interface (MI-BCI). The proposed novel model, based on EEGNet, matches the requirements of memory footprint and computational resources of low-power…
Brain-computer interface (BCI) systems are usually designed specifically for each subject based on motor imagery. Therefore, the usability of these networks has become a significant challenge. The network has to be designed separately for…
Research on Brain-Computer Interface (BCI) began in the 1970s and has increased in volume and diversified significantly since then. Today BCI is widely used for applications like assistive devices for physically challenged users, mental…
Brain-computer interfaces (BCIs) turn brain signals into functionally useful output, but they are not always accurate. A good Machine Learning classifier should be able to indicate how confident it is about a given classification, by giving…
Simulation-based training is an effective tool for acquiring practical skills, specifically to train new surgeons in a controlled and hazard-free environment, it is however important to measure participants cognitive load to decide whether…