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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 431440 of 466 papers

TitleStatusHype
BrainStratify: Coarse-to-Fine Disentanglement of Intracranial Neural Dynamics0
Brief Architectural Survey of Biopotential Recording Front-Ends since the 1970s0
Canonical Polyadic Decomposition with Auxiliary Information for Brain Computer Interface0
Capsule Attention for Multimodal EEG-EOG Representation Learning with Application to Driver Vigilance Estimation0
Channel Reflection: Knowledge-Driven Data Augmentation for EEG-Based Brain-Computer Interfaces0
Chromatic and High-frequency cVEP-based BCI Paradigm0
Classification and Recognition of Encrypted EEG Data Neural Network0
Classification of Distraction Levels Using Hybrid Deep Neural Networks From EEG Signals0
Classification of EEG Motor Imagery Using Deep Learning for Brain-Computer Interface Systems0
Classification of EEG Signal based on non-Gaussian Neutral Vector0
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