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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 151160 of 466 papers

TitleStatusHype
Reputation-Based Federated Learning Defense to Mitigate Threats in EEG Signal Classification0
EEG motor imagery decoding: A framework for comparative analysis with channel attention mechanismsCode1
A Convolutional Network Adaptation for Cortical Classification During Mobile Brain Imaging0
Automatic Control of Reactive Brain Computer Interfaces0
HappyFeat -- An interactive and efficient BCI framework for clinical applicationsCode1
Is controlling a brain-computer interface just a matter of presence of mind? The limits of cognitive-motor dissociation0
Unidirectional brain-computer interface: Artificial neural network encoding natural images to fMRI response in the visual cortexCode0
Phase Synchrony Component Self-Organization in Brain Computer Interface0
A Dynamic Domain Adaptation Deep Learning Network for EEG-based Motor Imagery Classification0
Brief Architectural Survey of Biopotential Recording Front-Ends since the 1970s0
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