Machine learning and its subfield deep learning techniques provide opportunities for the
development of operator mental state monitoring, especially for cognitive workload …

Graph theory analysis, a mathematical approach, has been applied in brain connectivity
studies to explore the organization of network patterns. The computation of graph theory …

Goal: This minireview aims to highlight recent important aspects to consider and evaluate
when passive brain-computer interface (pBCI) systems would be developed and used in …

In the nascent field of neuroergonomics, mental workload assessment is one of the most
important issues and has an apparent significance in real-world applications. Although prior …

Efficient classification of mental workload, an important issue in neuroscience, is limited, so
far to single task, while cross-task classification remains a challenge. Furthermore, network …

Despite the apparent usefulness of efficient mental workload assessment in various real-
world situations, the underlying neural mechanism remains largely unknown, and studies of …

Maintaining sustained attention during a prolonged cognitive task often comes at a cost:
high levels of mental fatigue. Heuristically, mental fatigue refers to a feeling of tiredness or …

The human brain is a large-scale system of functionally connected brain regions. This
system can be modeled as a network, or graph, by dividing the brain into a set of regions, or …

Evaluation of cognitive workload finds its application in many areas, from educational
program assessment through professional driver health examination to monitoring the …

This paper provides a focused and organized review of the research progress on
neurophysiological indicators, also called “neurometrics,” to show how they can effectively …