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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 211220 of 466 papers

TitleStatusHype
Brain informed transfer learning for categorizing construction hazards0
Motor imagery classification using EEG spectrograms0
Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision DecodingCode2
Towards Fast Single-Trial Online ERP based Brain-Computer Interface using dry EEG electrodes and neural networks: a pilot studyCode0
Embedding neurophysiological signalsCode0
Stimulus-Informed Generalized Canonical Correlation Analysis of Stimulus-Following Brain ResponsesCode0
FingerFlex: Inferring Finger Trajectories from ECoG signalsCode1
Toward the application of XAI methods in EEG-based systems0
A Transformer-based deep neural network model for SSVEP classificationCode1
Deep learning for ECoG brain-computer interface: end-to-end vs. hand-crafted features0
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