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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 7180 of 466 papers

TitleStatusHype
Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral FeaturesCode0
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
Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer InterfacesCode0
Evaluation Of P300 Speller Performance Using Large Language Models Along With Cross-Subject TrainingCode0
Feature Weighting and Regularization of Common Spatial Patterns in EEG-Based Motor Imagery BCICode0
EEGMobile: Enhancing Speed and Accuracy in EEG-Based Gaze Prediction with Advanced Mobile ArchitecturesCode0
An algorithm for onset detection of linguistic segments in continuous electroencephalogram signalsCode0
Embedding neurophysiological signalsCode0
Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer InterfacesCode0
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