Towards decoding motor imagery from EEG signal using optimized back propagation neural network with honey badger algorithm

Towards decoding motor imagery from EEG signal using optimized back propagation neural network with honey badger algorithm

Abstract The importance of using Brain-Computer Interface (BCI) systems based on electro encephalography (EEG) signal to decode Motor Imagery(MI) is very impressive because of the possibility of analyzing and translating brain signals related to movement intentions. This technology has many applicat...

Full description

Saved in:
Bibliographic Details
Main Authors: Zainab Hadi-Saleh, Mohammad Mosleh, Mohamed Adel Al-Shahe, Mahdi Mosleh
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Classification
Electroencephalography (EEG)
Motor Imagery(MI)
Machine learning
Back propagation neural network (BPNN)
Online Access:https://doi.org/10.1038/s41598-025-05423-0
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-05423-0

Similar Items