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Brain Computer Interface

A Brain-Computer Interface (BCI), also known as a Brain-Machine Interface (BMI), is a technology that enables direct communication between the brain and an external device, such as a computer or a machine, without the need for any muscular or peripheral nerve activity. Essentially, BCIs establish a direct pathway between the brain and an external device, allowing for bidirectional communication.

BCIs typically work by detecting and interpreting brain signals, which are then translated into commands that control external devices or provide feedback to the user. These brain signals can be detected through various methods, including electroencephalography (EEG), which measures electrical activity in the brain through electrodes placed on the scalp, or invasive techniques such as implanted electrodes.

Papers

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Showing 351–400 of 466 papers

TitleStatusHype
Non-invasive two-step strategy BCI: brain-muscle-hand interface—0
Offline EEG-Based Driver Drowsiness Estimation Using Enhanced Batch-Mode Active Learning (EBMAL) for Regression—0
On-device Learning of EEGNet-based Network For Wearable Motor Imagery Brain-Computer Interface—0
On improving learning capability of ELM and an application to brain-computer interface—0
Online and Offline Domain Adaptation for Reducing BCI Calibration Effort—0
Online LDA based brain-computer interface system to aid disabled people—0
Online Optimization of Stimulation Speed in an Auditory Brain-Computer Interface under Time Constraints—0
On Questions of Predictability and Control of an Intelligent System Using Probabilistic State-Transitions—0
On The Effects Of Data Normalisation For Domain Adaptation On EEG Data—0
On the Handwriting Tasks' Analysis to Detect Fatigue—0
On the Vulnerability of CNN Classifiers in EEG-Based BCIs—0
Optimized EEG based mood detection with signal processing and deep neural networks for brain-computer interface—0
Optimized Feature Selection and Neural Network-Based Classification of Motor Imagery Using EEG Signals—0
Optimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization—0
Ownership and Agency of an Independent Supernumerary Hand Induced by an Imitation Brain-Computer Interface—0
Partial Maximum Correntropy Regression for Robust Trajectory Decoding from Noisy Epidural Electrocorticographic Signals—0
Personalized Continual EEG Decoding: Retaining and Transferring Knowledge—0
PFML-based Semantic BCI Agent for Game of Go Learning and Prediction—0
Phase Synchrony Component Self-Organization in Brain Computer Interface—0
Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets—0
Precision Enhancement in Sustained Visual Attention Training Platforms: Offline EEG Signal Analysis for Classifier Fine-Tuning—0
Prediction of Memory Retrieval Performance Using Ear-EEG Signals—0
PreMovNet: Pre-Movement EEG-based Hand Kinematics Estimation for Grasp and Lift task—0
Pretraining Large Brain Language Model for Active BCI: Silent Speech—0
Protecting Multiple Types of Privacy Simultaneously in EEG-based Brain-Computer Interfaces—0
Protecting Privacy of Users in Brain-Computer Interface Applications—0
Prototype-based Domain Generalization Framework for Subject-Independent Brain-Computer Interfaces—0
Pseudo-online framework for BCI evaluation: A MOABB perspective—0
Psychometry: An Omnifit Model for Image Reconstruction from Human Brain Activity—0
QSVM-QNN: Quantum Support Vector Machine Based Quantum Neural Network Learning Algorithm for Brain-Computer Interfacing Systems—0
Real or Virtual? Using Brain Activity Patterns to differentiate Attended Targets during Augmented Reality Scenarios—0
Real-Time Brain-Computer Interface Control of Walking Exoskeleton with Bilateral Sensory Feedback—0
Real-Time EEG Classification via Coresets for BCI Applications—0
Real Time Vigilance Detection using Frontal EEG—0
Reconfiguration of Brain Network between Resting-state and Oddball Paradigm—0
Reconfiguring motor circuits for a joint manual and BCI task—0
Reducing training requirements through evolutionary based dimension reduction and subject transfer—0
EPOC Emotiv EEG Basics—0
Reputation-Based Federated Learning Defense to Mitigate Threats in EEG Signal Classification—0
Research Advances and New Paradigms for Biology-inspired Spiking Neural Networks—0
Revisiting the Application of Feature Selection Methods to Speech Imagery BCI Datasets—0
Riemannian Geometry for the classification of brain states with intracortical brain-computer interfaces—0
Robust alignment of cross-session recordings of neural population activity by behaviour via unsupervised domain adaptation—0
Robust Feature Engineering Techniques for Designing Efficient Motor Imagery-Based BCI-Systems—0
Sample Dominance Aware Framework via Non-Parametric Estimation for Spontaneous Brain-Computer Interface—0
Second Order Bilinear Discriminant Analysis for single trial EEG analysis—0
SEE: Semantically Aligned EEG-to-Text Translation—0
Selection of Proper EEG Channels for Subject Intention Classification Using Deep Learning—0
Sequential Best-Arm Identification with Application to Brain-Computer Interface—0
SG-GAN: Fine Stereoscopic-Aware Generation for 3D Brain Point Cloud Up-sampling from a Single Image—0
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