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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 231–240 of 466 papers

TitleStatusHype
An intertwined neural network model for EEG classification in brain-computer interfaces—0
A Novel Semi-supervised Meta Learning Method for Subject-transfer Brain-computer Interface—0
Application of Common Spatial Patterns in Gravitational Waves Detection—0
An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works—0
Are Brain-Computer Interfaces Feasible with Integrated Photonic Chips?—0
ArEEG_Chars: Dataset for Envisioned Speech Recognition using EEG for Arabic Characters—0
ArEEG_Words: Dataset for Envisioned Speech Recognition using EEG for Arabic Words—0
ART: Artifact Removal Transformer for Reconstructing Noise-Free Multichannel Electroencephalographic Signals—0
A self-paced BCI system with low latency for motor imagery onset detection based on time series prediction paradigm—0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification—0
Show:102550
← PrevPage 24 of 47Next →

No leaderboard results yet.