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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 301310 of 466 papers

TitleStatusHype
X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback0
Domain Adaptation with Optimal Transport on the Manifold of SPD matrices0
In-Ear SpO2 for Classification of Cognitive Workload0
Information Theoretic Feature Transformation Learning for Brain Interfaces0
Integrating Biological and Machine Intelligence: Attention Mechanisms in Brain-Computer Interfaces0
Integrating Language-Image Prior into EEG Decoding for Cross-Task Zero-Calibration RSVP-BCI0
Interaction-Grounded Learning with Action-inclusive Feedback0
Interpretable Convolutional Neural Networks for Subject-Independent Motor Imagery Classification0
Interpretable Dual-Filter Fuzzy Neural Networks for Affective Brain-Computer Interfaces0
Inter-stimulus Interval Study for the Tactile Point-pressure Brain-computer Interface0
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