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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 11–20 of 466 papers

TitleStatusHype
AbsoluteNet: A Deep Learning Neural Network to Classify Cerebral Hemodynamic Responses of Auditory Processing—0
BrainStratify: Coarse-to-Fine Disentanglement of Intracranial Neural Dynamics—0
The Study of Human Preference Based on Integrated Analysis of N1 and LPP Components—0
QSVM-QNN: Quantum Support Vector Machine Based Quantum Neural Network Learning Algorithm for Brain-Computer Interfacing Systems—0
Unlocking Non-Invasive Brain-to-Text—0
Covariance Density Neural Networks—0
Real-Time Brain-Computer Interface Control of Walking Exoskeleton with Bilateral Sensory Feedback—0
Pretraining Large Brain Language Model for Active BCI: Silent Speech—0
Sub-Scalp Brain-Computer Interface Device Design and Fabrication—0
Multi-scale convolutional transformer network for motor imagery brain-computer interfaceCode2
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