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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

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Showing 281–290 of 466 papers

TitleStatusHype
Low-cost brain computer interface for everyday useCode1
EEGDnet: Fusing Non-Local and Local Self-Similarity for 1-D EEG Signal Denoising with 2-D Transformer—0
Online Optimization of Stimulation Speed in an Auditory Brain-Computer Interface under Time Constraints—0
EEG-based Classification of Drivers Attention using Convolutional Neural Network—0
Generating Music and Generative Art from Brain activity—0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification—0
Voxel selection framework based on meta-heuristic search and mutual information for brain decoding—0
Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis—0
DAL: Feature Learning from Overt Speech to Decode Imagined Speech-based EEG Signals with Convolutional Autoencoder—0
EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli ClassificationCode1
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