GitHub

EEG Motor Imagery Classification – Subject S008

This project was developed as part of a university course on Brain–Computer Interfaces (BCI). The course explores how brain signals can be recorded, processed and translated into meaningful commands ...
GitHub

EEG Motor Imagery Classification

The goal of this project is to classify EEG signals recorded during motor imagery tasks, i.e. when a subject imagines moving a limb (left or right hand). By decoding these imagined movements from ...
IEEE

A Spatio-Temporal Joint Feature Learning Method on 3D EEG Tensors for Motor Imagery Decoding

Abstract: Decoding motor imagery (MI) from electroencephalography (EEG) has attracted extensive interest in brain-computer interface (BCI). However, reliance on hand-crafted features or a single ...
IEEE

EEG Based Motor Imagery Signal Processing and Building a Classifier

Abstract: Brain Computer Interfaces(BCIs) enables direct communication between human imaginations and computers. Motor imagery-based electroencephalography (EEG) is the most dominant for developing ...
EurekAlert!

Topology-aware deep learning model enhances EEG-based motor imagery decoding

Researchers develop a novel topology-aware multiscale feature fusion network to enhance the accuracy and robustness of EEG-based motor imagery decoding Electroencephalography (EEG) is a fascinating ...
MSN による配信

Topology-aware deep learning model enhances EEG-based motor imagery decoding

Electroencephalography (EEG) is a fascinating noninvasive technique that measures and records the brain's electrical activity. It detects small electrical signals produced when neurons in the brain ...