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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 2130 of 466 papers

TitleStatusHype
Dareplane: A modular open-source software platform for BCI research with application in closed-loop deep brain stimulationCode1
MAD: Multi-Alignment MEG-to-Text DecodingCode1
Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery ClassificationCode1
Synthesizing EEG Signals from Event-Related Potential Paradigms with Conditional Diffusion ModelsCode1
Towards gaze-independent c-VEP BCI: A pilot studyCode1
S-JEPA: towards seamless cross-dataset transfer through dynamic spatial attentionCode1
Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial NetworksCode1
Brain-Conditional Multimodal Synthesis: A Survey and TaxonomyCode1
DTP-Net: Learning to Reconstruct EEG signals in Time-Frequency Domain by Multi-scale Feature ReuseCode1
EEG motor imagery decoding: A framework for comparative analysis with channel attention mechanismsCode1
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