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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 3140 of 466 papers

TitleStatusHype
EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli ClassificationCode1
FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer InterfaceCode1
Cross Task Neural Architecture Search for EEG Signal ClassificationsCode1
Closed loop BCI System for Cybathlon 2020Code1
Natural scene reconstruction from fMRI signals using generative latent diffusionCode1
CNN-based Approaches For Cross-Subject Classification in Motor Imagery: From The State-of-The-Art to DynamicNetCode1
Decoding Human Attentive States from Spatial-temporal EEG Patches Using TransformersCode1
Dareplane: A modular open-source software platform for BCI research with application in closed-loop deep brain stimulationCode1
A Deep Neural Network for SSVEP-based Brain-Computer InterfacesCode1
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
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