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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 276–300 of 466 papers

TitleStatusHype
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
Siamese Network with Dual Attention for EEG-Driven Social Learning: Bridging the Human-Robot Gap in Long-Tail Autonomous Driving—0
Simultaneous induction of SSMVEP and SMR Using a Gaiting video stimulus: a novel hybrid brain-computer interface—0
Source Aware Deep Learning Framework for Hand Kinematic Reconstruction using EEG Signal—0
Source Data Selection for Brain-Computer Interfaces based on Simple Features—0
Sparsistent Learning of Varying-coefficient Models with Structural Changes—0
Spatial Auditory Brain-computer Interface using Head Related Impulse Response—0
Spatial Filtering for EEG-Based Regression Problems in Brain-Computer Interface (BCI)—0
Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification—0
Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals—0
SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG—0
SPEAK YOUR MIND! Towards Imagined Speech Recognition With Hierarchical Deep Learning—0
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