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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 1120 of 466 papers

TitleStatusHype
PHemoNet: A Multimodal Network for Physiological SignalsCode2
Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision DecodingCode2
Multi-scale convolutional transformer network for motor imagery brain-computer interfaceCode2
https://arxiv.org/pdf/2409.07491Code2
Decoding Human Attentive States from Spatial-temporal EEG Patches Using TransformersCode1
A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interfaceCode1
Deep comparisons of Neural Networks from the EEGNet familyCode1
Cross Task Neural Architecture Search for EEG Signal ClassificationsCode1
Device JNEEG to convert Jetson Nano to brain-Computer interfaces. Short reportCode1
Natural scene reconstruction from fMRI signals using generative latent diffusionCode1
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