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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 8190 of 466 papers

TitleStatusHype
https://arxiv.org/pdf/2409.07491Code2
ART: Artifact Removal Transformer for Reconstructing Noise-Free Multichannel Electroencephalographic Signals0
PiEEG-16 to Measure 16 EEG Channels with Raspberry Pi for Brain-Computer Interfaces and EEG devicesCode2
MixNet: Joining Force of Classical and Modern Approaches Toward the Comprehensive Pipeline in Motor Imagery EEG ClassificationCode0
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery ClassificationCode3
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
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