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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 291300 of 466 papers

TitleStatusHype
Simultaneous induction of SSMVEP and SMR Using a Gaiting video stimulus: a novel hybrid brain-computer interface0
Source Aware Deep Learning Framework for Hand Kinematic Reconstruction using EEG Signal0
Source Data Selection for Brain-Computer Interfaces based on Simple Features0
Sparsistent Learning of Varying-coefficient Models with Structural Changes0
Spatial Auditory Brain-computer Interface using Head Related Impulse Response0
Spatial Filtering for EEG-Based Regression Problems in Brain-Computer Interface (BCI)0
Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification0
Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals0
SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG0
SPEAK YOUR MIND! Towards Imagined Speech Recognition With Hierarchical Deep Learning0
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