Abstract Evaluation of operator Mental Workload (MW) levels via ongoing
electroencephalogram (EEG) is quite promising in Human-Machine (HM) collaborative task …

In order to detect human operator performance degradation or breakdown, this paper
proposes an adaptive support vector machine-based method to classify operator mental …

This work presents a novel approach to detecting real-time changes in workload using heart
rate variability (HRV). We propose that for a given workload state, the values of HRV vary in …

This paper proposed two psychophysiological-data-driven classification frameworks for
operator functional states (OFS) assessment in safety-critical human-machine systems with …

The ability to detect anomalies in perceived stimuli is critical to a broad range of practical
and applied activities involving human operators. In this paper, we propose a real-time …

Real-time classification of eye movements offers an effective mode for human–machine
interaction, and many eye-based interfaces have been presented in the literature. However …

One of the main challenges in the industry is having trained and efficient operators in
manufacturing lines. Smart adaptive guidance systems are developed that offer assistance …

This paper elaborates on the novel intelligence assessment method using the brainwave
sub-band power ratio features. The study focuses only on the left hemisphere brainwave in …

In highly automated human-machine systems, human operator functional state (OFS)
prediction is an important approach to prevent accidents caused by operator fatigue, high …

We consider the problem of detecting temporal changes in the functional state of human
subjects due to varying levels of cognitive load using real-time psychophysiological data …