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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 131140 of 466 papers

TitleStatusHype
Wavelet Analysis of Noninvasive EEG Signals Discriminates Complex and Natural Grasp Types0
Stimulus-Informed Generalized Canonical Correlation Analysis for Group Analysis of Neural Responses to Natural StimuliCode0
Subject-Independent Deep Architecture for EEG-based Motor Imagery Classification0
A Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding0
Using i-vectors for subject-independent cross-session EEG transfer learning0
A Temporal-Spectral Fusion Transformer with Subject-Specific Adapter for Enhancing RSVP-BCI DecodingCode0
Brain-Conditional Multimodal Synthesis: A Survey and TaxonomyCode1
Multiagent Copilot Approach for Shared Autonomy between Human EEG and TD3 Deep Reinforcement Learning0
3D-CLMI: A Motor Imagery EEG Classification Model via Fusion of 3D-CNN and LSTM with Attention0
Brain Computer Interface Technology for Future Battlefield0
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