Functional Near-Infrared Spectroscopy (fNIRS) is an innovative and promising
neuroimaging modality for studying brain activity in real-world environments. While fNIRS …

Cognitive load theory suggests that overloading of working memory may negatively affect
the performance of human in cognitively demanding tasks. Evaluation of cognitive load is a …

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technology
for monitoring cerebral hemodynamic responses. Enhancing fNIRS classification can …

Typical convolutional neural networks (CNNs) are widely used to recognize a user's stress
state using the functional near-infrared spectroscopy (fNIRS), which is the latest brain …

Recently, modeling of decision making and control systems that include heterogeneous
smart sensing devices (machines) as well as human agents as participants is becoming an …

Background Post‐ischemic stroke executive impairment (PISEI) is a serious obstacle for
patients to returning to their society and is currently difficult to screen early and clinically …

Working memory load (WML) is one of the widely applied signals in the areas of human–
machine interaction. The precise evaluation of the WML is crucial for this kind of application …

Functional near-infrared spectroscopy (fNIRS) is a non-invasive, portable brain imaging
technology capable of objectively reflect cognitive states. Recently, Graph Convolutional …

Cognitive load (CL), defined as the mental effort required to process information, plays a
pivotal role in user performance and experience in various domains, particularly within …

Cognition is crucial to brain function, and accurately classifying cognitive load is essential for
understanding the psychological processes across tasks. This paper innovatively combines …