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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 3140 of 466 papers

TitleStatusHype
MVCNet: Multi-View Contrastive Network for Motor Imagery ClassificationCode1
SSVEP-BiMA: Bifocal Masking Attention Leveraging Native and Symmetric-Antisymmetric Components for Robust SSVEP Decoding0
CSSSTN: A Class-sensitive Subject-to-subject Semantic Style Transfer Network for EEG Classification in RSVP TasksCode0
Decoding Human Attentive States from Spatial-temporal EEG Patches Using TransformersCode1
ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks0
Interpretable Dual-Filter Fuzzy Neural Networks for Affective Brain-Computer Interfaces0
Easing Seasickness through Attention Redirection with a Mindfulness-Based Brain--Computer Interface0
Towards Probabilistic Inference of Human Motor Intentions by Assistive Mobile Robots Controlled via a Brain-Computer Interface0
Integrating Language-Image Prior into EEG Decoding for Cross-Task Zero-Calibration RSVP-BCI0
Human-AI Teaming Using Large Language Models: Boosting Brain-Computer Interfacing (BCI) and Brain Research0
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