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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 111–120 of 466 papers

TitleStatusHype
Brain-Computer Interface with Corrupted EEG Data: A Tensor Completion Approach—0
An embedding for EEG signals learned using a triplet loss—0
Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction—0
Brain Computer Interface Technology for Future Battlefield—0
Brain Computer Interface: Deep Learning Approach to Predict Human Emotion Recognition—0
A self-paced BCI system with low latency for motor imagery onset detection based on time series prediction paradigm—0
Comparison of Sub-Scalp EEG and Endovascular Stent-Electrode Array for Visual Evoked Potential Brain-Computer Interface—0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification—0
Confidence-Aware Subject-to-Subject Transfer Learning for Brain-Computer Interface—0
An Analysis of the Accuracy of the P300 BCI—0
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