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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 121130 of 466 papers

TitleStatusHype
Comparison of Sub-Scalp EEG and Endovascular Stent-Electrode Array for Visual Evoked Potential Brain-Computer Interface0
Covariate Shift Estimation based Adaptive Ensemble Learning for Handling Non-Stationarity in Motor Imagery related EEG-based Brain-Computer Interface0
CropCat: Data Augmentation for Smoothing the Feature Distribution of EEG Signals0
Cross-Correlation Based Discriminant Criterion for Channel Selection in Motor Imagery BCI Systems0
Canine EEG Helps Human: Cross-Species and Cross-Modality Epileptic Seizure Detection via Multi-Space Alignment0
Cross-Subject Deep Transfer Models for Evoked Potentials in Brain-Computer Interface0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification0
Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface0
A self-paced BCI system with low latency for motor imagery onset detection based on time series prediction paradigm0
Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction0
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