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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 441450 of 466 papers

TitleStatusHype
RISE-iEEG: Robust to Inter-Subject Electrodes Implantation Variability iEEG ClassifierCode0
Feature Weighting and Regularization of Common Spatial Patterns in EEG-Based Motor Imagery BCICode0
Towards Fast Single-Trial Online ERP based Brain-Computer Interface using dry EEG electrodes and neural networks: a pilot studyCode0
AI-based artistic representation of emotions from EEG signals: a discussion on fairness, inclusion, and aestheticsCode0
Using Riemannian geometry for SSVEP-based Brain Computer InterfaceCode0
Stimulus-Informed Generalized Canonical Correlation Analysis of Stimulus-Following Brain ResponsesCode0
CSSSTN: A Class-sensitive Subject-to-subject Semantic Style Transfer Network for EEG Classification in RSVP TasksCode0
Evaluating Fast Adaptability of Neural Networks for Brain-Computer InterfaceCode0
PhyAAt: Physiology of Auditory Attention to Speech DatasetCode0
Minima Possible Weights: A Homogenous Deep Ensemble Method for Cross-Subject Motor Imagery ClassificationCode0
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