This paper reviews published papers related to neurophysiological measurements (
electroencephalography: EEG, electrooculography EOG; heart rate: HR) in pilots/drivers …

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

Mental workload assessment is essential for maintaining human health and preventing
accidents. Most research on this issue is limited to a single task. However, cross-task …

Forming connections between human performance and design, this new edition of
Engineering Psychology and Human Performance examines human–machine interaction …

Neuroergonomics is an emerging science that is defined as the study of the human brain in
relation to performance at work and in everyday settings. This paper provides a critical …

This paper describes an open access electroencephalography (EEG) data set for
multitasking mental workload activity induced by a single-session simultaneous capacity …

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

Using machine-learning methodologies to analyze EEG signals becomes increasingly
attractive for recognizing human emotions because of the objectivity of physiological data …

This paper presents an investigation about the effects of mental stress on prefrontal cortex
(PFC) subregions using simultaneous measurement of functional Near-Infrared …

An accurate measure of mental workload level has diverse neuroergonomic applications
ranging from brain computer interfacing to improving the efficiency of human operators. In …