Papers Brain Computer Interface
“Brain Computer Interface” 태그가 달린 논문 466편 · 필터 해제
Speech Imagery BCI Training Using Game with a Purpose
Games are used in multiple fields of brain–computer interface (BCI) research and applications to improve participants’ engagement and enjoyment during electroencephalogram (EEG) data collection. However, despite potentia…
Brain Computer InterfaceEEGElectroencephalogram (EEG)Beware of Overestimated Decoding Performance Arising from Temporal Autocorrelations in Electroencephalogram Signals
Researchers have reported high decoding accuracy (>95%) using non-invasive Electroencephalogram (EEG) signals for brain-computer interface (BCI) decoding tasks like image decoding, emotion recognition, auditory spatial a…
Brain Computer InterfaceEEGEeg DecodingElectroencephalogram (EEG)+2High Performance P300 Spellers Using GPT2 Word Prediction With Cross-Subject Training
Amyotrophic lateral sclerosis (ALS) severely impairs patients' ability to communicate, often leading to a decline in their quality of life within a few years of diagnosis. The P300 speller brain-computer interface (BCI) …
Brain Computer InterfaceEEGSubject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery Classification
Electroencephalography (EEG) motor imagery (MI) classification is a fundamental, yet challenging task due to the variation of signals between individuals i.e., inter-subject variability. Previous approaches try to mitiga…
Brain Computer InterfaceEEGMotor ImageryTransfer LearningNeuroAssist: Enhancing Cognitive-Computer Synergy with Adaptive AI and Advanced Neural Decoding for Efficient EEG Signal Classification
Traditional methods of controlling prosthetics frequently encounter difficulties regarding flexibility and responsiveness, which can substantially impact people with varying cognitive and physical abilities. Advancements…
Brain Computer InterfaceEEGEEG Signal ClassificationMotor ImageryJNEEG shield for Jetson Nano for real-time EEG signal processing with deep learning
The article presents an accessible route into the field of neuroscience through the JNEEG device. This device allows converting the Jetson Nano board into a brain-computer interface, making it easy to measure EEG, EMG, a…
Brain Computer InterfaceEEGEEG2TEXT: Open Vocabulary EEG-to-Text Decoding with EEG Pre-Training and Multi-View Transformer
Deciphering the intricacies of the human brain has captivated curiosity for centuries. Recent strides in Brain-Computer Interface (BCI) technology, particularly using motor imagery, have restored motor functions such as …
Brain Computer InterfaceEEGMotor ImageryPrecision Enhancement in Sustained Visual Attention Training Platforms: Offline EEG Signal Analysis for Classifier Fine-Tuning
In this study, a novel open-source brain-computer interface (BCI) platform was developed to decode scalp electroencephalography (EEG) signals associated with sustained attention. The EEG signal collection was conducted u…
Brain Computer InterfaceEEGERPQuantifying Spatial Domain Explanations in BCI using Earth Mover's Distance
Brain-computer interface (BCI) systems facilitate unique communication between humans and computers, benefiting severely disabled individuals. Despite decades of research, BCIs are not fully integrated into clinical and …
Brain Computer Interfacechannel selectionEEGMotor ImageryUnveiling Thoughts: A Review of Advancements in EEG Brain Signal Decoding into Text
The conversion of brain activity into text using electroencephalography (EEG) has gained significant traction in recent years. Many researchers are working to develop new models to decode EEG signals into text form. Alth…
Brain Computer InterfaceEEGOptimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization
Brain-computer interface systems and the recording of brain activity has garnered significant attention across a diverse spectrum of applications. EEG signals have emerged as a modality for recording neural electrical ac…
Brain Computer Interfacechannel selectionEEGEEG Signal Classification+2Evaluating Fast Adaptability of Neural Networks for Brain-Computer Interface
Electroencephalography (EEG) classification is a versatile and portable technique for building non-invasive Brain-computer Interfaces (BCI). However, the classifiers that decode cognitive states from EEG brain data perfo…
Brain Computer InterfaceDomain AdaptationEEGMeta-Learning+1MindArm: Mechanized Intelligent Non-Invasive Neuro-Driven Prosthetic Arm System
Currently, individuals with arm mobility impairments (referred to as "patients") face limited technological solutions due to two key challenges: (1) non-invasive prosthetic devices are often prohibitively expensive and c…
Brain Computer InterfaceEEGElectroencephalogram (EEG)Psychometry: An Omnifit Model for Image Reconstruction from Human Brain Activity
Reconstructing the viewed images from human brain activity bridges human and computer vision through the Brain-Computer Interface. The inherent variability in brain function between individuals leads existing literature …
Brain Computer InterfaceImage ReconstructionMixture-of-ExpertsSpecificitySynthesizing EEG Signals from Event-Related Potential Paradigms with Conditional Diffusion Models
Data scarcity in the brain-computer interface field can be alleviated through the use of generative models, specifically diffusion models. While diffusion models have previously been successfully applied to electroenceph…
Brain Computer InterfaceEEGElectroencephalogram (EEG)SpecificityTowards gaze-independent c-VEP BCI: A pilot study
A limitation of brain-computer interface (BCI) spellers is that they require the user to be able to move the eyes to fixate on targets. This poses an issue for users who cannot voluntarily control their eye movements, fo…
Brain Computer InterfaceEEGS-JEPA: towards seamless cross-dataset transfer through dynamic spatial attention
Motivated by the challenge of seamless cross-dataset transfer in EEG signal processing, this article presents an exploratory study on the use of Joint Embedding Predictive Architectures (JEPAs). In recent years, self-sup…
Brain Computer InterfaceBrain DecodingEEGERP+4Uncertainty Quantification for cross-subject Motor Imagery classification
Uncertainty Quantification aims to determine when the prediction from a Machine Learning model is likely to be wrong. Computer Vision research has explored methods for determining epistemic uncertainty (also known as mod…
Brain Computer InterfaceClassificationMotor ImageryUncertainty QuantificationTransferring BCI models from calibration to control: Observing shifts in EEG features
Public Motor Imagery-based brain-computer interface (BCI) datasets are being used to develop increasingly good classifiers. However, they usually follow discrete paradigms where participants perform Motor Imagery at regu…
Brain Computer InterfaceEEGMotor ImageryGeometric Neural Network based on Phase Space for BCI-EEG decoding
Objective: The integration of Deep Learning (DL) algorithms on brain signal analysis is still in its nascent stages compared to their success in fields like Computer Vision. This is particularly true for BCI, where the b…
Brain Computer InterfaceEEGEeg Decoding