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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 171–180 of 466 papers

TitleStatusHype
EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning—0
EEG-Based Speech Decoding: A Novel Approach Using Multi-Kernel Ensemble Diffusion Models—0
Deep Learning Decoding of Mental State in Non-invasive Brain Computer Interface—0
EEG-BBNet: a Hybrid Framework for Brain Biometric using Graph Connectivity—0
Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button—0
Deep learning-based classification of fine hand movements from low frequency EEG—0
Brain Computer Interface Technology for Future Battlefield—0
EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks—0
Brain-Computer Interface with Corrupted EEG Data: A Tensor Completion Approach—0
Deep Learning Architecture for Motor Imaged Words—0
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