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Titlebook: Human Mental Workload: Models and Applications; Second International Luca Longo,M. Chiara Leva Conference proceedings 2019 Springer Nature

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Mental Workload in the Explanation of Automation Effects on ATC Performance analyse, predict, and mitigate these negative effects by assessing the complexity of ATC in relation to the mental workload experienced by the controller. Hence, a highly complex situation will be one with a high mental workload and a low complex situation will be one in which the mental workload is low.
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Understanding, Supporting, and Redesigning Cognitive Workbe used to understand work and mental workload. The work domain, control task, and strategies analysis can be useful to understand the nature of work, work allocation and mental workload. Finally, the prediction of work patterns is discussed. Predicting the influence of new technologies on human wor
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Assessing Workload in Human-Machine Teams from Psychophysiological Data with Sparse Ground Truthtruth comprising self-reported measures of actual workload. However, it is often not feasible to elicit self-assessed workload ratings with great frequency. As part of an ongoing effort to improve the effectiveness of human-machine teams through real-time human workload monitoring, we explore the ut
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Developing an Objective Indicator of Fatigue: An Alternative Mobile Version of the Psychomotor Vigile mobile version of the ‘gold standard’ Psychomotor Vigilance Task (PVT) could be used to provide an objective indicator of fatigue in staff working in applied safety critical settings such as train driving, hospital staffs, emergency services, law enforcements, etc., using different mobile devices.
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Workload Assessment Using Speech-Related Neck Surface Electromyographye cognitive workload assessment. A retrospective analysis of anterior neck sEMG signals, recorded from 10 subjects during a time-pressured mental arithmetic task with verbal responses during a previous study by Stepp et al. [.], suggests that a measure known as neck intermuscular beta coherence (NIB
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Analysing the Impact of Machine Learning to Model Subjective Mental Workload: A Case Study in Third- models are aimed at aggregating those factors, believed to shape mental workload, and their interaction, for the purpose of human performance prediction. In the literature, models are mainly theory-driven: their distinct development has been influenced by the beliefs and intuitions of individual sc
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Latency Differences Between Mental Workload Measures in Detecting Workload Changesological measures. Although we would expect a certain degree of convergence, research has shown that the emergence of disassociations and insensitivities between measures is very frequent. One possible explanation could be related to the differing latencies between each workload assessment method. W
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