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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 181190 of 466 papers

TitleStatusHype
Deep Learning Decoding of Mental State in Non-invasive Brain Computer Interface0
EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network0
Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button0
Deep learning-based classification of fine hand movements from low frequency EEG0
Deep Learning Architecture for Motor Imaged Words0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG0
EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units0
EEG Right & Left Voluntary Hand Movement-based Virtual Brain-Computer Interfacing Keyboard Using Hybrid Deep Learning Approach0
Autoregressive models for biomedical signal processing0
A Multi-Context Character Prediction Model for a Brain-Computer Interface0
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