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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 311320 of 466 papers

TitleStatusHype
Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding0
Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface0
In the realm of hybrid Brain: Human Brain and AI0
Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition0
ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks0
Is controlling a brain-computer interface just a matter of presence of mind? The limits of cognitive-motor dissociation0
JNEEG shield for Jetson Nano for real-time EEG signal processing with deep learning0
Kullback-Leibler Penalized Sparse Discriminant Analysis for Event-Related Potential Classification0
Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees0
Learning Patterns in Imaginary Vowels for an Intelligent Brain Computer Interface (BCI) Design0
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