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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 5160 of 466 papers

TitleStatusHype
BEATS: An Open-Source, High-Precision, Multi-Channel EEG Acquisition Tool SystemCode1
Brain-Conditional Multimodal Synthesis: A Survey and TaxonomyCode1
Deep comparisons of Neural Networks from the EEGNet familyCode1
Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial NetworksCode1
A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interfaceCode1
S-JEPA: towards seamless cross-dataset transfer through dynamic spatial attentionCode1
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEGCode1
Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery ClassificationCode1
The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation ModelsCode1
T-TIME: Test-Time Information Maximization Ensemble for Plug-and-Play BCIsCode1
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