相关论文: Online classification of imagined speech using fun…
Brain-computer interface (BCI) is the technology that enables the communication between humans and devices by reflecting status and intentions of humans. When conducting imagined speech, the users imagine the pronunciation as if actually…
Speech-related Brain Computer Interface (BCI) technologies provide effective vocal communication strategies for controlling devices through speech commands interpreted from brain signals. In order to infer imagined speech from active…
This work explores the possibility of decoding Imagined Speech (IS) signals which can be used to create a new design of Human-Computer Interface (HCI). Since the underlying process generating EEG signals is unknown, various feature…
An asynchronous Brain--Computer Interface (BCI) based on imagined speech is a tool that allows to control an external device or to emit a message at the moment the user desires to by decoding EEG signals of imagined speech. In order to…
The mission of visual brain-computer interfaces (BCIs) is to enhance information transfer rate (ITR) to reach high speed towards real-life communication. Despite notable progress, noninvasive visual BCIs have encountered a plateau in ITRs,…
The prevalence of online learning poses a vital challenge in real-time monitoring of students' concentration. Traditional methods such as questionnaire assessments require manual intervention, and webcam-based monitoring fails to provide…
Brain-computer interfaces (BCIs) have shown promise in enabling communication for individuals with motor impairments. Recent advancements like brain-to-speech technology aim to reconstruct speech from neural activity. However, decoding…
Brain Computer Interface (BCI) can help patients of neuromuscular diseases restore parts of the movement and communication abilities that they have lost. Most of BCIs rely on mapping brain activities to device instructions, but limited…
In this work, we explore the possibility of decoding Imagined Speech brain waves using machine learning techniques. We propose a covariance matrix of Electroencephalogram channels as input features, projection to tangent space of covariance…
Brain computer interface applications can be used to overcome learning problems, especially student anxiety, lack of focus, and lack of attention. This paper introduces a system based on brain computer interface (BCI) to be used in…
This study examines the effectiveness of traditional machine learning classifiers versus deep learning models for detecting the imagined speech using electroencephalogram data. Specifically, we evaluated conventional machine learning…
Electroencephalogram (EEG) based brain-computer interfaces (BCI) may provide a means of communication for those affected by severe paralysis. However, the relatively low information transfer rates (ITR) of these systems, currently limited…
Brain-computer interface (BCI) research, while promising, has largely been confined to static and fixed environments, limiting real-world applicability. To move towards practical BCI, we introduce a real-time wireless imagined speech…
Brain-Computer Interfaces enable direct communication between the brain and external systems, with functional Near-Infrared Spectroscopy emerging as a portable and non-invasive method for capturing cerebral hemodynamics. This study…
Brain-computer interface (BCI) is one of the tools which enables the communication between humans and devices by reflecting intention and status of humans. With the development of artificial intelligence, the interest in communication…
Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive form of Brain-Computer Interface (BCI). It is used for the imaging of brain hemodynamics and has gained popularity due to the certain pros it poses over other similar…
New mental tasks were investigated for suitability in Brain-Computer Interface (BCI). Electroencephalography (EEG) signals were collected and analyzed to identify these mental tasks. MS Windows-based software was developed for investigating…
Imagined speech is spotlighted as a new trend in the brain-machine interface due to its application as an intuitive communication tool. However, previous studies have shown low classification performance, therefore its use in real-life is…
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 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…