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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 281290 of 466 papers

TitleStatusHype
Deep Learning in fNIRS: A review0
Enhanced motor imagery-based EEG classification using a discriminative graph Fourier subspace0
Deep Optimal Transport for Domain Adaptation on SPD ManifoldsCode0
Application of Common Spatial Patterns in Gravitational Waves Detection0
Automatic Muscle Artifacts Identification and Removal from Single-Channel EEG Using Wavelet Transform with Meta-heuristically Optimized Non-local Means Filter0
Neural Network-Based Feature Extraction for Multi-Class Motor Imagery Classification0
A Survey on Brain-Computer Interaction0
Learning shared neural manifolds from multi-subject FMRI data0
Confidence-Aware Subject-to-Subject Transfer Learning for Brain-Computer Interface0
Interpretable Convolutional Neural Networks for Subject-Independent Motor Imagery Classification0
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