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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 421430 of 466 papers

TitleStatusHype
Towards Real-World BCI: CCSPNet, A Compact Subject-Independent Motor Imagery FrameworkCode0
Quantifying Spatial Domain Explanations in BCI using Earth Mover's DistanceCode0
Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigmsCode0
Source-Free Domain Adaptation for SSVEP-based Brain-Computer InterfacesCode0
An algorithm for onset detection of linguistic segments in continuous electroencephalogram signalsCode0
Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCICode0
Complex common spatial patterns on time-frequency decomposed EEG for brain-computer interfaceCode0
Uncertainty Quantification for cross-subject Motor Imagery classificationCode0
Classification of High-Dimensional Motor Imagery Tasks based on An End-to-end role assigned convolutional neural networkCode0
Recurrent Neural Networks for P300-based BCICode0
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