Human-centricity, a core value of Industry 5.0, places humans in the center of production. It
leads to the prioritization of human needs, spanning from health and safety to self …

The ever-increasing number of computing devices around us results in more and more
systems competing for our attention, making cognitive workload a crucial factor for the user …

Artificial intelligence (AI) has generated a plethora of new opportunities, potential and
challenges for understanding and supporting learning. In this paper, we position human and …

This study utilized multimodal learning analytics and AI-based methods to examine the
patterns of the socially shared regulation of collaborative learning (CL). The study involved …

Recently, the coronavirus disease 2019 (COVID-19) pandemic has led to rapid digitalisation
in education, requiring educators to adopt several technologies simultaneously for online …

Entering the 5G and internet of things (IoT) era, human–machine interfaces (HMIs) capable
of providing humans with more intuitive interaction with the digitalized world have …

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

Skin lesion diagnosis is a key step for skin cancer screening, which requires high accuracy
and interpretability. Though many computer-aided methods, especially deep learning …

This paper compares the three levels of data fusion with the goal of determining the optimal
level of data fusion for multi-sensor human activity data. Using the data processing pipeline …

Current brain cognitive models are insufficient in handling outliers and dynamics of
electroencephalogram (EEG) signals. This article presents a novel self-paced dynamic …