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 401410 of 466 papers

TitleStatusHype
ArEEG_Words: Dataset for Envisioned Speech Recognition using EEG for Arabic Words0
ART: Artifact Removal Transformer for Reconstructing Noise-Free Multichannel Electroencephalographic Signals0
A self-paced BCI system with low latency for motor imagery onset detection based on time series prediction paradigm0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification0
A Spiking Neural Network based on Neural Manifold for Augmenting Intracortical Brain-Computer Interface Data0
A Study on Stroke Rehabilitation through Task-Oriented Control of a Haptic Device via Near-Infrared Spectroscopy-Based BCI0
A Subject-Independent Brain-Computer Interface Framework Based on Supervised Autoencoder0
A Survey on Brain-Computer Interaction0
A Survey on Deep Learning-based Non-Invasive Brain Signals:Recent Advances and New Frontiers0
A Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding0
Show:102550
← PrevPage 41 of 47Next →

No leaderboard results yet.