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 141150 of 466 papers

TitleStatusHype
Beware of Overestimated Decoding Performance Arising from Temporal Autocorrelations in Electroencephalogram Signals0
AbsoluteNet: A Deep Learning Neural Network to Classify Cerebral Hemodynamic Responses of Auditory Processing0
Domain Adaptation with Optimal Transport on the Manifold of SPD matrices0
Detecting Driver's Distraction using Long-term Recurrent Convolutional Network0
An Adaptive Contrastive Learning Model for Spike Sorting0
Adaptive neural network classifier for decoding MEG signals0
Bayesian Nonparametric Models for Synchronous Brain-Computer Interfaces0
Bayesian Networks for Brain-Computer Interfaces: A Survey0
An Accurate EEGNet-based Motor-Imagery Brain-Computer Interface for Low-Power Edge Computing0
A Brain-Computer Interface Augmented Reality Framework with Auto-Adaptive SSVEP Recognition0
Show:102550
← PrevPage 15 of 47Next →

No leaderboard results yet.