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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 411420 of 466 papers

TitleStatusHype
Adaptive neural network classifier for decoding MEG signals0
Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration0
Agreement Rate Initialized Maximum Likelihood Estimator for Ensemble Classifier Aggregation and Its Application in Brain-Computer Interface0
Offline EEG-Based Driver Drowsiness Estimation Using Enhanced Batch-Mode Active Learning (EBMAL) for Regression0
Covariate Shift Estimation based Adaptive Ensemble Learning for Handling Non-Stationarity in Motor Imagery related EEG-based Brain-Computer Interface0
Mining within-trial oscillatory brain dynamics to address the variability of optimized spatial filtersCode0
Feature Weighting and Regularization of Common Spatial Patterns in EEG-Based Motor Imagery BCICode0
A Technique Based on Chaos for Brain Computer Interfacing0
Multiclass Common Spatial Pattern for EEG based Brain Computer Interface with Adaptive Learning Classifier0
Human and Smart Machine Co-Learning with Brain Computer Interface0
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