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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 151160 of 466 papers

TitleStatusHype
Classification and Recognition of Encrypted EEG Data Neural Network0
Chromatic and High-frequency cVEP-based BCI Paradigm0
An intertwined neural network model for EEG classification in brain-computer interfaces0
Channel Reflection: Knowledge-Driven Data Augmentation for EEG-Based Brain-Computer Interfaces0
Capsule Attention for Multimodal EEG-EOG Representation Learning with Application to Driver Vigilance Estimation0
A New Method for Features Normalization in Motor Imagery Few-Shot Learning using Resting-State0
Canonical Polyadic Decomposition with Auxiliary Information for Brain Computer Interface0
A neuro-inspired system for online learning and recognition of parallel spike trains, based on spike latency and heterosynaptic STDP0
A GA-based feature selection of the EEG signals by classification evaluation: Application in BCI systems0
A3E: Aligned and Augmented Adversarial Ensemble for Accurate, Robust and Privacy-Preserving EEG Decoding0
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