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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 131140 of 466 papers

TitleStatusHype
ART: Artifact Removal Transformer for Reconstructing Noise-Free Multichannel Electroencephalographic Signals0
Classifying Single-Trial EEG during Motor Imagery with a Small Training Set0
ArEEG_Words: Dataset for Envisioned Speech Recognition using EEG for Arabic Words0
A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network0
A Consumer BCI for Automated Music Evaluation Within a Popular On-Demand Music Streaming Service - Taking Listener's Brainwaves to Extremes0
Classification of Visual Perception and Imagery based EEG Signals Using Convolutional Neural Networks0
Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis0
ArEEG_Chars: Dataset for Envisioned Speech Recognition using EEG for Arabic Characters0
Are Brain-Computer Interfaces Feasible with Integrated Photonic Chips?0
Classification of fNIRS Data Under Uncertainty: A Bayesian Neural Network Approach0
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