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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

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Showing 201–210 of 466 papers

TitleStatusHype
Evaluating a Semi-Autonomous Brain-Computer Interface Based on Conformal Geometric Algebra and Artificial Vision—0
Classification and Recognition of Encrypted EEG Data Neural Network—0
Evaluation of Classical Features and Classifiers in Brain-Computer Interface Tasks—0
Classification of Distraction Levels Using Hybrid Deep Neural Networks From EEG Signals—0
Classification of EEG Motor Imagery Using Deep Learning for Brain-Computer Interface Systems—0
Factorization Approach for Sparse Spatio-Temporal Brain-Computer Interface—0
Automatic Control of Reactive Brain Computer Interfaces—0
Classification of EEG Signal based on non-Gaussian Neutral Vector—0
A multi-agent control framework for co-adaptation in brain-computer interfaces—0
Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration—0
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