相关论文: The N400 for Brain Computer Interfacing: complexit…

We introduce a novel auditory brain-computer interface (BCI) paradigm, Auditory Intention Decoding (AID), designed to enhance communication capabilities within the brain-AI interface (BAI) system EEGChat. AID enables users to select among…

Designing a feedback that helps participants to achieve higher performances is an important concern in brain-computer interface (BCI) research. In a pilot study, we demonstrate how a congruent auditory feedback could improve classification…

Brain-computer interfaces (BCIs) use brain signals such as electroencephalography to reflect user intention and enable two-way communication between computers and users. BCI technology has recently received much attention in healthcare…

Brain-Computer Interfaces (BCIs) based on P300 event-related potentials offer promising applications in health, education, and assistive technologies. However, challenges related to inter- and intra-subject variability and the…

There are high technological and software demands associated with conducting brain-computer interface (BCI) research. In order to accelerate the development and accessibility of BCI, it is worthwhile to focus on open-source and desired…

In this study, we adopted visual motion imagery, which is a more intuitive brain-computer interface (BCI) paradigm, for decoding the intuitive user intention. We developed a 3-dimensional BCI training platform and applied it to assist the…

Mental Imagery based Brain-Computer Interfaces (MI-BCI) enable their users to control an interface, e.g., a prosthesis, by performing mental imagery tasks only, such as imagining a right arm movement while their brain activity is measured…

Computational paralinguistic analysis is increasingly being used in a wide range of cyber applications, including security-sensitive applications such as speaker verification, deceptive speech detection, and medical diagnostics. While…

In this paper we introduce the combined use of Brain-Computer Interfaces (BCI) and Haptic interfaces. We propose to adapt haptic guides based on the mental activity measured by a BCI system. This novel approach is illustrated within a…

Brain-computer interfaces (BCI) are an important mode of alternative and augmentative communication for many people. Unlike keyboards, many BCI systems do not display even the 26 letters of English at one time, let alone all the symbols in…

Brain-Computer Interfaces (BCIs) suffer from high inter-subject variability and limited labeled data, often requiring lengthy calibration phases. In this work, we present an end-to-end approach that explicitly models the subject dependency…

Despite many years of research, the quest to identify neural correlates of perceptual consciousness (NCC) remains unresolved. One major obstacle lies in methodological limitations: most studies rely on non-invasive neural measures with…

With the development of artificial intelligence and unmanned equipment, human-machine hybrid formations will be the main focus in future combat formations. With the development of big data and various situational awareness technologies,…

Event coreference resolution is an important research problem with many applications. Despite the recent remarkable success of pretrained language models, we argue that it is still highly beneficial to utilize symbolic features for the…

Brain-computer interfaces (BCIs) have the potential to significantly change the ways in which humans interact with technology, the environment, and even each other. Unfortunately, BCI technologies are seldom robust enough for use in…

Effective connectivity (EC), indicative of the causal interactions between brain regions, is fundamental to understanding information processing in the brain. Traditional approaches, which infer EC from neural responses to stimulations, are…

Researchers increasingly explore deploying brain-computer interfaces (BCIs) for able-bodied users, with the motivation of accessing mental states more directly than allowed by existing body-mediated interaction. This motivation seems to…

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…

In this paper, we propose a conceptual framework for personalized brain-computer interface (BCI) applications, which can offer an enhanced user experience by customizing services to individual preferences and needs, based on endogenous…

Neurocognitive disorders (NCDs), such as Alzheimer's disease, are globally prevalent and require scalable screening methods for proactive management. Prior research has explored the potential of technologies like conversational AI (CAI) to…