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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 231240 of 466 papers

TitleStatusHype
An intertwined neural network model for EEG classification in brain-computer interfaces0
Physics-inform attention temporal convolutional network for EEG-based motor imagery classificationCode2
How does artificial intelligence contribute to iEEG research?0
Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeXCode1
EPOC Emotiv EEG Basics0
Factorization Approach for Sparse Spatio-Temporal Brain-Computer Interface0
Interaction-Grounded Learning with Action-inclusive Feedback0
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEGCode1
A Neural-Inspired Architecture for EEG-Based Auditory Attention Detection0
Classification of EEG Motor Imagery Using Deep Learning for Brain-Computer Interface Systems0
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