In this article, a contemporary tack of mental tasks on cognitive parts of humans is appraised
using two different approaches such as wavelet transforms at a discrete time (DWT) and …

The accurate evaluation of mental workload of operators in human machine systems is of
great significance in ensuring the safety of operators and the correct execution of tasks …

Advancements in portable neuroimaging technologies open up new opportunities to gain
insight into the neural dynamics and cognitive processes underlying day-to-day behaviors …

Objective The event-related potential (ERP) methods based on laboratory control scenes
have been widely used to measure the level of mental workload during operational tasks. In …

Objective This study aimed to examine the impact of non-driving-related tasks (NDRTs) on
drivers in highly automated driving scenarios and sought to develop a deep learning model …

Research on cross-task EEG signals analysis methods has become a fast-growing research
hotspot. In recent years, more and more researchers applied the features, which were widely …

Electroencephalography (EEG) microstate analysis has become a popular tool for studying
the spatial and temporal dynamics of large‐scale electrophysiological activities in the brain …

Introduction A well-designed brain-computer interface (BCI) can make accurate and reliable
predictions of a user's state through the passive assessment of their brain activity; in turn …

Everyday tasks demand attentional resources to perceive, process, and respond to
important information. Attempting to complete multiple tasks simultaneously, that is …

This research presents a novel methodology for objective and personalized workload
assessment of human operators within manual control tasks. The proposed method …