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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

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Showing 181–190 of 466 papers

TitleStatusHype
EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features—0
EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network—0
EEG-Based Speech Decoding: A Novel Approach Using Multi-Kernel Ensemble Diffusion Models—0
EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning—0
Brain-based control of car infotainment—0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—0
EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units—0
EEG Right & Left Voluntary Hand Movement-based Virtual Brain-Computer Interfacing Keyboard Using Hybrid Deep Learning Approach—0
An amplitudes-perturbation data augmentation method in convolutional neural networks for EEG decoding—0
EEG-based Classification of Drivers Attention using Convolutional Neural Network—0
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