Mental Fatigue Assessment in Demanding Marine Operations

Inhaltsverzeichnis

1. Frontmatter

2. Chapter 1. Introduction

   Thiago Gabriel Monteiro, Houxiang Zhang

   Abstract

   Maritime operations are more demanding every day. New and complex marine operations include anchor-handling operations at depths of several thousand meters, 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 systems, including vessels, cranes, winches, and remotely operated vehicles. This increasing complexity brings an attending increase in the risk of accidents and the damaged caused by them. The majority of accidents in the maritime domain are related to Human factors (HF) challenges. To make maritime operations safer, it is essential that the ones that are the most relevant among these challenges need to be identified and addressed.

3. Chapter 2. Handling Fatigue

   Thiago Gabriel Monteiro, Houxiang Zhang

   Abstract

   There is no single accepted definition of the different types of fatigue a person can experience, but MF (cognitive impairment), physical fatigue and 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 essential role in fatigue mitigation and physiological recovery and inadequate sleep cycles can lead to or worsen fatigue scenarios. When considering task related fatigue, it can arise from passiveness (boring tasks) or activeness (high workload). A person in more likely to fall asleep when the task at hand is dull or boring or not requiring a lot of interaction. In the other hand, in a hectic environment a person is less prone to fall sleep, but the high workload can lead to fatigue build up.

4. 3. Mental Fatigue Assessment Sensor Framework

   Thiago Gabriel Monteiro, Houxiang Zhang

   Abstract

   This chapter describes the proposed MFA framework, going over the requirements of such systems and detailing their implementation for the actual framework, including hardware and software integration. This chapter also approaches the experimental setup applied in all case studies, which will be discussed in the following chapters.

5. 4. Mental Fatigue Assessment Using Artificial Intelligence

   Thiago Gabriel Monteiro, Houxiang Zhang

   Abstract

   Data-driven methods have increased in popularity in recent years, and successful applications of NN in highly diverse areas of research have driven the 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.

6. 5. Model-Based Assessment for Multi-subject and Multi-task Scenarios

   Thiago Gabriel Monteiro, Houxiang Zhang

   Abstract

   The previous chapter explored the application of CNN, to MFA. The CNN performed well in multi-subject scenarios when considering only two possible MF states: non-fatigue and fatigue. When including a more discretized MF scale, such as using the KSS levels as reference, CNN was only satisfactory for single subject-scenarios. To address these deficiencies, this chapter investigates a model-based MFA approach for multi-task and multi-subject scenarios.

7. 6. Mental Fatigue Prediction

   Thiago Gabriel Monteiro, Houxiang Zhang

   Abstract

   Assessing seafarers’ MF levels helps identifying potential operational risks and the ability to simulate future scenarios can be used during planning and management, to ensure safer operational conditions. In this chapter, we propose a framework for modelling seafarers’ future MF levels using a combination of both physiological and environmental sensors and model- and data-based techniques. We will establish the building blocks of this framework and present examples of how it could be applied in different scenarios as soon as enough data is collected to feed the data-based section of the model. Once properly trained, this framework could be used not only to assess human-related operational risks but also to provide the necessary information to ensure that these issues are addressed before potential danger escalates to real accidents. This chapter does not aim to solve the MFP problem, but only to provide a starting point for further developments.

8. Chapter 7. Research Challenges

   Thiago Gabriel Monteiro, Houxiang Zhang

   Abstract

   The number of published works studying MFA has steadily increased in the recent years [1]. This increase reflects a change of paradigm in human machine 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 a steady increase in accidents.

9. 8. Correction to: Mental Fatigue Assessment in Demanding Marine Operations

   Thiago Gabriel Monteiro, Houxiang Zhang