Over the last few decades, the Brain-Computer Interfaces have been gradually making their
way to the epicenter of scientific interest. Many scientists from all around the world have …

A wearable system for the personalized EEG-based detection of engagement in learning 4.0
is proposed. In particular, the effectiveness of the proposed solution is assessed by means …

Biocybernetic loops encompass users' state detection and system adaptation based on
physiological signals. Current adaptive systems limit the adaptation to task features such as …

Operators of complex systems across multiple domains (eg, aviation, automotive, and
nuclear power industry) are required to perform their tasks over prolonged and continuous …

The detection of the cognitive tasks performed by a subject during data acquisition of a
neuroimaging method has a wide range of applications: functioning of brain-computer …

When, why, and how are people motivated? This is the essential question that motivation
science has sought to address since the field's inception, and yet motivation scientists have …

The industry increasingly insists on academic cooperation to solve the identified problems
such as workers' performance, wellbeing, job satisfaction, and injuries. It causes an unsafe …

Despite recent advances in deep neural models for semantic image editing, present
approaches are dependent on explicit human input. Previous work assumes the availability …

The aptitude-oriented exercises from almost all domains impose cognitive load on their
operators. Evaluating such load poses several challenges owing to many factors like …

The ideal brain–computer interface (BCI) adapts to the user's state to enable optimal BCI
performance. Two methods of BCI adaptation are commonly applied: User-centered design …