Related papers: Comparing fingers and gestures for bci control usi…
Patients with extreme forms of paralysis face challenges in communication, adversely impacting their quality of life. Recent studies have reported higher-than-chance performance in decoding handwritten letters from EEG signals, potentially…
A Brain Computer Interface (BCI) is a communication system that receives neurological signals from the brain and translates them into control commands for electrical (e.g., computer mouse) and electromechanical (e.g., Wheelchair) devices.…
Brain-computer interface (BCI) decodes brain signals to understand user intention and status. Because of its simple and safe data acquisition process, electroencephalogram (EEG) is commonly used in non-invasive BCI. One of EEG paradigms,…
Brain-computer interface (BCI) technology enables direct communication between the brain and external devices, allowing individuals to control their environment using brain signals. However, existing BCI approaches face three critical…
Hemispheric strokes impair motor control in contralateral body parts, necessitating effective rehabilitation strategies. Motor Imagery-based Brain-Computer Interfaces (MI-BCIs) promote neuroplasticity, aiding the recovery of motor…
Accurate finger force estimation is critical for next-generation human-machine interfaces. Traditional electromyography (EMG)-based decoding methods using deep learning require large datasets and high computational resources, limiting their…
Motor brain-computer interfaces (BCIs) are a promising technology that may enable motor-impaired people to interact with their environment. Designing real-time and accurate BCI is crucial to make such devices useful, safe, and easy to use…
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…
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…
Brain-computer interfaces (BCIs) offer a pathway to restore communication for individuals with severe motor or speech impairments. Imagined handwriting provides an intuitive paradigm for character-level neural decoding, bridging the gap…
While intracortical Brain-Computer Interfaces (iBCIs) that decode imagined handwriting have achieved high communication rates for Latin scripts, they rely on observing every character in the alphabet during training. This poses a challenge…
Kinematics decoding from brain activity helps in developing rehabilitation or power-augmenting brain-computer interface devices. Low-frequency signals recorded from non-invasive electroencephalography (EEG) are associated with the neural…
While invasively recorded brain activity is known to provide detailed information on motor commands, it is an open question at what level of detail information about positions of body parts can be decoded from non-invasively acquired…
A brain-computer interface (BCI) may be used to control a prosthetic or orthotic hand using neural activity from the brain. The core of this sensorimotor BCI lies in the interpretation of the neural information extracted from…
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…
Brain computer interface is the current area of research to provide assistance to disabled persons. To cope up with the growing needs of BCI applications, this paper presents an automated classification scheme for handgrip actions on…
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…
Myoelectric interfaces enable intuitive and natural control by decoding residual muscle activity, providing an effective pathway for motor restoration in individuals with preserved musculature. However, in patients with severe muscular…
This study introduces a pioneering approach in brain-computer interface (BCI) technology, featuring our novel concept of high-level visual imagery for non-invasive electroencephalography (EEG)-based communication. High-level visual imagery,…
Restoring naturalistic finger control in assistive technologies requires the continuous decoding of motor intent with high accuracy, efficiency, and robustness. Here, we present a spike-based decoding framework that integrates spiking…