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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 4150 of 466 papers

TitleStatusHype
Transfer Learning of an Ensemble of DNNs for SSVEP BCI Spellers without User-Specific TrainingCode1
Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeXCode1
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEGCode1
BEATS: An Open-Source, High-Precision, Multi-Channel EEG Acquisition Tool SystemCode1
Priming Cross-Session Motor Imagery Classification with A Universal Deep Domain Adaptation FrameworkCode1
A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interfaceCode1
Functional connectivity ensemble method to enhance BCI performance (FUCONE)Code1
Low-cost brain computer interface for everyday useCode1
EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli ClassificationCode1
Transformer-based Spatial-Temporal Feature Learning for EEG DecodingCode1
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