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 251260 of 466 papers

TitleStatusHype
Optimized EEG based mood detection with signal processing and deep neural networks for brain-computer interface0
Optimized Feature Selection and Neural Network-Based Classification of Motor Imagery Using EEG Signals0
Optimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization0
Ownership and Agency of an Independent Supernumerary Hand Induced by an Imitation Brain-Computer Interface0
Partial Maximum Correntropy Regression for Robust Trajectory Decoding from Noisy Epidural Electrocorticographic Signals0
Personalized Continual EEG Decoding: Retaining and Transferring Knowledge0
PFML-based Semantic BCI Agent for Game of Go Learning and Prediction0
Phase Synchrony Component Self-Organization in Brain Computer Interface0
Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets0
Precision Enhancement in Sustained Visual Attention Training Platforms: Offline EEG Signal Analysis for Classifier Fine-Tuning0
Show:102550
← PrevPage 26 of 47Next →

No leaderboard results yet.