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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 251–275 of 466 papers

TitleStatusHype
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
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