Related papers: A New Generation of Brain-Computer Interface Based…
We introduce Brain-Artificial Intelligence Interfaces (BAIs) as a new class of Brain-Computer Interfaces (BCIs). Unlike conventional BCIs, which rely on intact cognitive capabilities, BAIs leverage the power of artificial intelligence to…
In individuals afflicted with conditions such as paralysis, the implementation of Brain-Computer-Interface (BCI) has begun to significantly impact their quality of life. Furthermore, even in healthy individuals, the anticipated advantages…
Advancements in clinical Brain-Computer Interfaces (BCIs) depend on precise and reliable signal interpretation. However, the high-dimensional and noisy nature of data captured from both implanted and non-implanted BCIs poses significant…
Noninvasive brain-computer interface (BCI) is widely used to recognize users' intentions. Especially, BCI related to tactile and sensation decoding could provide various effects on many industrial fields such as manufacturing advanced touch…
This short technical report describes the approach submitted to the Clinical BCI Challenge-WCCI2020. This submission aims to classify motor imagery task from EEG signals and relies on Riemannian Geometry, with a twist. Instead of using the…
Correlation matrices are fundamental summaries of functional brain networks, yet standard analyses often treat entries independently, ignoring the curved geometry of correlation space. Existing geometric methods frequently lack closed-form…
Brain computer interface (BCI) provides promising applications in neuroprosthesis and neurorehabilitation by controlling computers and robotic devices based on the patient's intentions. Here, we have developed a novel BCI platform that…
Nowadays, the possibility to run advanced AI on embedded systems allows natural interaction between humans and machines, especially in the automotive field. We present a custom portable EEG-based Brain-Computer Interface (BCI) that exploits…
Motor imagery-based brain-computer interfaces (BCIs) use an individuals ability to volitionally modulate localized brain activity as a therapy for motor dysfunction or to probe causal relations between brain activity and behavior. However,…
Toward user-driven Metaverse applications with fast wireless connectivity and tremendous computing demand through future 6G infrastructures, we propose a Brain-Computer Interface (BCI) enabled framework that paves the way for the creation…
BCIs have significantly improved the patients' quality of life by restoring damaged hearing, sight, and movement capabilities. After evolving their application scenarios, the current trend of BCI is to enable new innovative brain-to-brain…
Brain-Computer Interfaces (BCIs) are used in various application scenarios allowing direct communication between the brain and computers. Specifically, electroencephalography (EEG) is one of the most common techniques for obtaining evoked…
Human-machine interactions are being increasingly explored to create alternative ways of communication and to improve our daily life. Based on a classification of the user's intention from the user's underlying neural activity,…
While search technologies have evolved to be robust and ubiquitous, the fundamental interaction paradigm has remained relatively stable for decades. With the maturity of the Brain-Machine Interface, we build an efficient and effective…
This paper aims at identifying emerging computational intelligence trends for the design and modeling of complex biometric-enabled infrastructure and systems. Biometric-enabled systems are evolving towards deep learning and deep inference…
The inter/intra-subject variability of electroencephalography (EEG) makes the practical use of the brain-computer interface (BCI) difficult. In general, the BCI system requires a calibration procedure to acquire subject/session-specific…
The integration of brain-computer interfaces (BCIs) into the realm of smart wheelchair (SW) technology signifies a notable leap forward in enhancing the mobility and autonomy of individuals with physical disabilities. BCIs are a technology…
Multimodal functional neuroimaging enables systematic analysis of brain mechanisms and provides discriminative representations for brain-computer interface (BCI) decoding. However, its acquisition is constrained by high costs and…
A brain-computer interface (BCI) based on the motor imagery (MI) paradigm translates one's motor intention into a control signal by classifying the Electroencephalogram (EEG) signal of different tasks. However, most existing systems either…
Brain-Machine Interfaces (BMIs) have recently emerged as a clinically viable option to restore voluntary movements after paralysis. These devices are based on the ability to extract information about movement intent from neural signals…