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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 131140 of 466 papers

TitleStatusHype
ART: Artifact Removal Transformer for Reconstructing Noise-Free Multichannel Electroencephalographic Signals0
MixNet: Joining Force of Classical and Modern Approaches Toward the Comprehensive Pipeline in Motor Imagery EEG ClassificationCode0
Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural DynamicsCode0
Research Advances and New Paradigms for Biology-inspired Spiking Neural Networks0
On-device Learning of EEGNet-based Network For Wearable Motor Imagery Brain-Computer Interface0
Emotion-Agent: Unsupervised Deep Reinforcement Learning with Distribution-Prototype Reward for Continuous Emotional EEG Analysis0
EEG Right & Left Voluntary Hand Movement-based Virtual Brain-Computer Interfacing Keyboard Using Hybrid Deep Learning Approach0
RISE-iEEG: Robust to Inter-Subject Electrodes Implantation Variability iEEG ClassifierCode0
EEGMobile: Enhancing Speed and Accuracy in EEG-Based Gaze Prediction with Advanced Mobile Architectures0
Domain Adaptation-Enhanced Searchlight: Enabling classification of brain states from visual perception to mental imageryCode0
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