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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 1120 of 466 papers

TitleStatusHype
Physics-inform attention temporal convolutional network for EEG-based motor imagery classificationCode2
Raspberry PI Shield - for measure EEG (PIEEG)Code2
Brain-Computer-Interface controlled robot via RaspberryPi and PiEEGCode2
GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery SignalsCode2
AGTCNet: A Graph-Temporal Approach for Principled Motor Imagery EEG ClassificationCode1
TCANet: A Temporal Convolutional Attention Network for Motor Imagery EEG DecodingCode1
Spatial Distillation based Distribution Alignment (SDDA) for Cross-Headset EEG ClassificationCode1
MVCNet: Multi-View Contrastive Network for Motor Imagery ClassificationCode1
Decoding Human Attentive States from Spatial-temporal EEG Patches Using TransformersCode1
T-TIME: Test-Time Information Maximization Ensemble for Plug-and-Play BCIsCode1
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