Advanced computational intelligence using electroencephalogram-based brain functional connectivity in monitoring cognitive workload

Abstract

Electroencephalography-based analysis using functional connectivity has been used to study various aspects of brain function including cognitive workload. This thesis aims to investigate the role of brain functional connectivity in detecting cognitive workload. The results of this research facilitate the development of methods for detecting changes in sustained attention, with applications in detecting driver fatigue in automotive contexts and workload in aviation contexts. This research will contribute to our understanding of the neural mechanisms underlying different mental workload states and provide new insights into the development of technologies for enhancing cognitive performance and safety in various real-world domains.