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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
Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer InterfacesCode0
An algorithm for onset detection of linguistic segments in continuous electroencephalogram signalsCode0
Embedding neurophysiological signalsCode0
Exploring Embedding Methods in Binary Hyperdimensional Computing: A Case Study for Motor-Imagery based Brain-Computer InterfacesCode0
Evaluating Fast Adaptability of Neural Networks for Brain-Computer InterfaceCode0
Improving SSVEP BCI Spellers With Data Augmentation and Language ModelsCode0
Benchmarking framework for machine learning classification from fNIRS dataCode0
Deep Optimal Transport for Domain Adaptation on SPD ManifoldsCode0
EEG-DCNet: A Fast and Accurate MI-EEG Dilated CNN Classification MethodCode0
Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigmsCode0
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