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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 6170 of 466 papers

TitleStatusHype
Improving SSVEP BCI Spellers With Data Augmentation and Language ModelsCode0
Minima Possible Weights: A Homogenous Deep Ensemble Method for Cross-Subject Motor Imagery ClassificationCode0
AI-based artistic representation of emotions from EEG signals: a discussion on fairness, inclusion, and aestheticsCode0
Geometric Neural Network based on Phase Space for BCI-EEG decodingCode0
Mining within-trial oscillatory brain dynamics to address the variability of optimized spatial filtersCode0
FOIT: Fast Online Instance Transfer for Improved EEG Emotion RecognitionCode0
Feature Weighting and Regularization of Common Spatial Patterns in EEG-Based Motor Imagery BCICode0
Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer InterfacesCode0
Evaluation Of P300 Speller Performance Using Large Language Models Along With Cross-Subject TrainingCode0
Aggregating Intrinsic Information to Enhance BCI Performance through Federated LearningCode0
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