SOTAVerified

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 381390 of 466 papers

TitleStatusHype
AM-MTEEG: Multi-task EEG classification based on impulsive associative memory0
A multi-agent control framework for co-adaptation in brain-computer interfaces0
A Multi-Context Character Prediction Model for a Brain-Computer Interface0
An Accurate EEGNet-based Motor-Imagery Brain-Computer Interface for Low-Power Edge Computing0
An Adaptive Contrastive Learning Model for Spike Sorting0
Adaptive Subspace Sampling for Class Imbalance Processing-Some clarifications, algorithm, and further investigation including applications to Brain Computer Interface0
Analysis of artifacts in EEG signals for building BCIs0
An amplitudes-perturbation data augmentation method in convolutional neural networks for EEG decoding0
An Analysis of the Accuracy of the P300 BCI0
An embedding for EEG signals learned using a triplet loss0
Show:102550
← PrevPage 39 of 47Next →

No leaderboard results yet.