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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 4150 of 466 papers

TitleStatusHype
EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli ClassificationCode1
EEG-Inception: An Accurate and Robust End-to-End Neural Network for EEG-based Motor Imagery ClassificationCode1
FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer InterfaceCode1
FingerFlex: Inferring Finger Trajectories from ECoG signalsCode1
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
LMDA-Net:A lightweight multi-dimensional attention network for general EEG-based brain-computer interface paradigms and interpretabilityCode1
Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial NetworksCode1
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEGCode1
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