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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
HappyFeat -- An interactive and efficient BCI framework for clinical applicationsCode1
LMDA-Net:A lightweight multi-dimensional attention network for general EEG-based brain-computer interface paradigms and interpretabilityCode1
Natural scene reconstruction from fMRI signals using generative latent diffusionCode1
EEG Synthetic Data Generation Using Probabilistic Diffusion ModelsCode1
Deep comparisons of Neural Networks from the EEGNet familyCode1
Device JNEEG to convert Jetson Nano to brain-Computer interfaces. Short reportCode1
Closed loop BCI System for Cybathlon 2020Code1
FingerFlex: Inferring Finger Trajectories from ECoG signalsCode1
A Transformer-based deep neural network model for SSVEP classificationCode1
Cross Task Neural Architecture Search for EEG Signal ClassificationsCode1
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