Titlebook: Mental Fatigue Assessment in Demanding Marine Operations; Thiago Gabriel Monteiro,Houxiang Zhang Book 2024 The Editor(s) (if applicable) a

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Correction to: Mental Fatigue Assessment in Demanding Marine Operations,

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Book 2024task. Among the different architectures tested, convolutional neural networks (CNN) showed the best performance when dealing with multiple physiological data channels. Optimization was used to improve the performance of CNN in the cross-subject MFA task. Testing different combinations of physiologic

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Introduction,eters, precise installation of subsea modules weighing hundreds of tons, and platform support in icy and cold environments on northern regions. Further increasing the level of complexity of these operations, they require greater coordination among professionals operating disparate mechanisms and sys

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Handling Fatigue,sleepiness are frequently cited in several studies [1]. In this study we are going to consider sleepiness as a consequence of fatigue, either mental or physical. Fatigue can be originated from mainly two different sources. It can be sleep (or lack of sleep) related or task related. Sleep play an ess

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Mental Fatigue Assessment Using Artificial Intelligence,e trend. MF-related research is no exception. This chapter investigates the use of NN, especially CNN, for MFA. Different architectures and sensor combinations are tested and MFA approaches are proposed.

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Research Challenges,e systems as machinery systems become increasingly reliable and consequently human operators account for a steady increase in accidents. This increase reflects a change of paradigm in human machine systems as machinery systems become increasingly reliable and consequently human operators account for