Papers Brain Computer Interface
“Brain Computer Interface” 태그가 달린 논문 466편 · 필터 해제
Siamese Network with Dual Attention for EEG-Driven Social Learning: Bridging the Human-Robot Gap in Long-Tail Autonomous Driving
Robots with wheeled, quadrupedal, or humanoid forms are increasingly integrated into built environments. However, unlike human social learning, they lack a critical pathway for intrinsic cognitive development, namely, le…
Autonomous DrivingBrain Computer InterfaceDynamic Time WarpingEEG+2Riemannian Geometry for the classification of brain states with intracortical brain-computer interfaces
This study investigates the application of Riemannian geometry-based methods for brain decoding using invasive electrophysiological recordings. Although previously employed in non-invasive, the utility of Riemannian geom…
BenchmarkingBrain Computer InterfaceBrain DecodingOptimized Feature Selection and Neural Network-Based Classification of Motor Imagery Using EEG Signals
Objective: Machine learning- and deep learning-based models have recently been employed in motor imagery intention classification from electroencephalogram (EEG) signals. Nevertheless, there is a limited understanding of…
Brain Computer InterfaceEEGElectroencephalogram (EEG)feature selection+1EEG2GAIT: A Hierarchical Graph Convolutional Network for EEG-based Gait Decoding
Decoding gait dynamics from EEG signals presents significant challenges due to the complex spatial dependencies of motor processes, the need for accurate temporal and spectral feature extraction, and the scarcity of high…
Brain Computer InterfaceEEGEdge-Fog Computing-Enabled EEG Data Compression via Asymmetrical Variational Discrete Cosine Transform Network
The large volume of electroencephalograph (EEG) data produced by brain-computer interface (BCI) systems presents challenges for rapid transmission over bandwidth-limited channels in Internet of Things (IoT) networks. To …
Brain Computer InterfaceData CompressionEEGVariational InferenceOn Questions of Predictability and Control of an Intelligent System Using Probabilistic State-Transitions
One of the central aims of neuroscience is to reliably predict the behavioral response of an organism using its neural activity. If possible, this implies we can causally manipulate the neural response and design brain-c…
Brain Computer InterfaceSpatial Distillation based Distribution Alignment (SDDA) for Cross-Headset EEG Classification
A non-invasive brain-computer interface (BCI) enables direct interaction between the user and external devices, typically via electroencephalogram (EEG) signals. However, decoding EEG signals across different headsets re…
Brain Computer InterfaceDomain AdaptationEEGElectroencephalogram (EEG)+3Integrating Biological and Machine Intelligence: Attention Mechanisms in Brain-Computer Interfaces
With the rapid advancement of deep learning, attention mechanisms have become indispensable in electroencephalography (EEG) signal analysis, significantly enhancing Brain-Computer Interface (BCI) applications. This paper…
Brain Computer InterfaceEEGRepresentation LearningMotor Imagery EEG Signals: Multi-Task Classification and Subject Identification with a Lightweight CNN
Motor imagery is a domain of the brain-computer interface where individuals imagine moving their body parts without any physical movement occurring. This field has significant applications in enhancing abilities in indiv…
Binary ClassificationBrain Computer InterfaceEEGMotor ImageryMVCNet: Multi-View Contrastive Network for Motor Imagery Classification
Electroencephalography (EEG)-based brain-computer interfaces (BCIs) enable neural interaction by decoding brain activity for external communication. Motor imagery (MI) decoding has received significant attention due to i…
Brain Computer InterfaceContrastive LearningData AugmentationEEG+3Minima Possible Weights: A Homogenous Deep Ensemble Method for Cross-Subject Motor Imagery Classification
Motor Imagery (MI) systems in Brain-Computer Interface (BCI) research provide communication and control solutions for individuals with motor impairments, yet cross-subject classification remains challenging due to subst…
Brain Computer InterfaceEnsemble LearningMotor ImageryTest-time AdaptationSSVEP-BiMA: Bifocal Masking Attention Leveraging Native and Symmetric-Antisymmetric Components for Robust SSVEP Decoding
Brain-computer interface (BCI) based on steady-state visual evoked potentials (SSVEP) is a popular paradigm for its simplicity and high information transfer rate (ITR). Accurate and fast SSVEP decoding is crucial for rel…
Brain Computer InterfaceSSVEPCSSSTN: A Class-sensitive Subject-to-subject Semantic Style Transfer Network for EEG Classification in RSVP Tasks
The Rapid Serial Visual Presentation (RSVP) paradigm represents a promising application of electroencephalography (EEG) in Brain-Computer Interface (BCI) systems. However, cross-subject variability remains a critical cha…
Brain Computer InterfaceEEGStyle TransferDecoding Human Attentive States from Spatial-temporal EEG Patches Using Transformers
Learning the spatial topology of electroencephalogram (EEG) channels and their temporal dynamics is crucial for decoding attention states. This paper introduces EEG-PatchFormer, a transformer-based deep learning framewor…
Brain Computer InterfaceEEGElectroencephalogram (EEG)ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks
Cross-subject variability in EEG degrades performance of current deep learning models, limiting the development of brain-computer interface (BCI). This paper proposes ISAM-MTL, which is a multi-task learning (MTL) EEG cl…
Brain Computer InterfaceClassificationEEGFew-Shot Learning+2Interpretable Dual-Filter Fuzzy Neural Networks for Affective Brain-Computer Interfaces
Fuzzy logic provides a robust framework for enhancing explainability, particularly in domains requiring the interpretation of complex and ambiguous signals, such as brain-computer interface (BCI) systems. Despite signifi…
Brain Computer InterfaceDecision MakingEEGEasing Seasickness through Attention Redirection with a Mindfulness-Based Brain--Computer Interface
Seasickness is a prevalent issue that adversely impacts both passenger experiences and the operational efficiency of maritime crews. While techniques that redirect attention have proven effective in alleviating motion si…
Brain Computer InterfaceEEGTowards Probabilistic Inference of Human Motor Intentions by Assistive Mobile Robots Controlled via a Brain-Computer Interface
Assistive mobile robots are a transformative technology that helps persons with disabilities regain the ability to move freely. Although autonomous wheelchairs significantly reduce user effort, they still require human i…
Brain Computer InterfaceEEGGenerative Adversarial NetworkIntegrating Language-Image Prior into EEG Decoding for Cross-Task Zero-Calibration RSVP-BCI
Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interface (BCI) is an effective technology used for information detection by detecting Event-Related Potentials (ERPs). The current RSVP decoding methods can p…
Brain Computer InterfaceEEGEeg DecodingImage RetrievalHuman-AI Teaming Using Large Language Models: Boosting Brain-Computer Interfacing (BCI) and Brain Research
Recently, there is an increasing interest in using artificial intelligence (AI) to automate aspects of the research process, or even autonomously conduct the full research cycle from idea generation, over data analysis, …
Brain Computer InterfaceEEGMotor ImageryTransfer Learning