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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

Showing 5175 of 466 papers

TitleStatusHype
Functional connectivity ensemble method to enhance BCI performance (FUCONE)Code1
Natural scene reconstruction from fMRI signals using generative latent diffusionCode1
AGTCNet: A Graph-Temporal Approach for Principled Motor Imagery EEG ClassificationCode1
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
BEATS: An Open-Source, High-Precision, Multi-Channel EEG Acquisition Tool SystemCode1
Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial NetworksCode1
A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interfaceCode1
LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer InterfaceCode1
TCANet: A Temporal Convolutional Attention Network for Motor Imagery EEG DecodingCode1
S-JEPA: towards seamless cross-dataset transfer through dynamic spatial attentionCode1
MixNet: Joining Force of Classical and Modern Approaches Toward the Comprehensive Pipeline in Motor Imagery EEG ClassificationCode0
Minima Possible Weights: A Homogenous Deep Ensemble Method for Cross-Subject Motor Imagery ClassificationCode0
Mining within-trial oscillatory brain dynamics to address the variability of optimized spatial filtersCode0
AI-based artistic representation of emotions from EEG signals: a discussion on fairness, inclusion, and aestheticsCode0
Improving SSVEP BCI Spellers With Data Augmentation and Language ModelsCode0
Geometric Neural Network based on Phase Space for BCI-EEG decodingCode0
Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer InterfacesCode0
Aggregating Intrinsic Information to Enhance BCI Performance through Federated LearningCode0
Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral FeaturesCode0
Feature Weighting and Regularization of Common Spatial Patterns in EEG-Based Motor Imagery BCICode0
FOIT: Fast Online Instance Transfer for Improved EEG Emotion RecognitionCode0
PhyAAt: Physiology of Auditory Attention to Speech DatasetCode0
Embedding neurophysiological signalsCode0
Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer InterfacesCode0
EEGMobile: Enhancing Speed and Accuracy in EEG-Based Gaze Prediction with Advanced Mobile ArchitecturesCode0
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