Enhanced Cognitive Load Detection in Air Traffic Control Operators Using EEG and a Hybrid Deep Learning Approach

Enhanced Cognitive Load Detection in Air Traffic Control Operators Using EEG and a Hybrid Deep Learning Approach

The automatic and effective detection of cognitive load for air traffic control (ATC) operators through electroencephalography (EEG) signals provides a covert and objective method for enhancing ATC safety. Nevertheless, the extant paradigm is limited to simple cognitive tasks and lacks real-world sc...

Full description

Saved in:
Bibliographic Details
Main Authors: Yueying Zhou, Junji Jiang, Lijun Wang, Shanshan Liang, Hao Liu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Air traffic control
EEG
load detection
self-attention
CNN
brain mechanisms
Online Access:https://ieeexplore.ieee.org/document/10843192/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/10843192/

Similar Items