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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
Raspberry PI Shield - for measure EEG (PIEEG)Code2
Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision DecodingCode2
Neuro-GPT: Towards A Foundation Model for EEGCode2
Multi-scale convolutional transformer network for motor imagery brain-computer interfaceCode2
Brain-Conditional Multimodal Synthesis: A Survey and TaxonomyCode1
A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interfaceCode1
Natural scene reconstruction from fMRI signals using generative latent diffusionCode1
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
Deep comparisons of Neural Networks from the EEGNet familyCode1
Device JNEEG to convert Jetson Nano to brain-Computer interfaces. Short reportCode1
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