Dimitrios Konovessis

EEG-based Mental Workload and Stress Recognition of Crew Members in Maritime Virtual Simulator: A Case Study

Many studies have shown that the majority of maritime accidents/incidents are attributed to human errors as the initiating cause. Efforts have been made to study human factors that can result in a safer maritime transportation. Among all techniques, Electroencephalogram (EEG) has the advantages such as high time resolution, possibility to continuously monitor brain states with high accuracy, recognition of human mental workload, emotion, stress, vigilance, etc. In this paper, we designed and carried out an experiment to collect the EEG signals to study stress and sharing of the mental workload among crew members during collaboration tasks performance on the ships bridge virtual simulator. Four maritime trainees were monitored in the experiment. Each of them had a role such as an officer on watch, captain, pilot, or steersman. The results show that the captain had the highest stress and workload. However, the other three trainees experienced low workload and stress due to shared work and responsibility. The EEG is a promising evaluation tool to be used in the human factors study in the maritime domain.

EEG-Based Mental Workload and Stress Monitoring of Crew Members in Maritime Virtual Simulator

Many studies have shown that most maritime accidents are attributed to human error as the initiating cause, resulting in a need for study of human factors to improve safety in maritime transportation. Among the various techniques, Electroencephalography (EEG) has the key advantage of high time resolution, with the possibility to continuously monitor brain states including human mental workload, emotions, stress levels, etc. In this paper, we proposed a novel mental workload recognition algorithm using deep learning techniques that outperformed the state-of art algorithms and successfully applied it to monitor crew members’ brain states in a maritime simulator. We designed and carried out an experiment to collect the EEG data, which was used to study stress and distribution of mental workload among crew members during collaborative tasks in the ship’s bridge simulator. The experiment consisted of two parts. In part 1, 3 maritime trainees fulfilled the tasks with and without an experienced captain. The results of EEG analyses showed that 2 out of 3 trainees had less workload and stress when the experienced captain was present. In part 2, 4 maritime trainees collaborated with each other in the simulator. Our findings showed that the trainee who acted as the captain had the highest stress and workload levels while the other three trainees experienced low workload and stress due to the shared work and responsibility. These results suggest that EEG is a promising evaluation tool applicable in human factors study for the maritime domain.

A review of offshore decommissioning regulations in five countries – Strengths and weaknesses

Abstract The decommissioning of offshore structures around the world will be a persisting problem in the coming decades as many structures will exceed their shelf life, or when reservoirs are no longer productive. This paper examines an overview of the global offshore decommissioning legal regime, and a summary of regulations in countries that are deemed to be more experienced in decommissioning such as the UK, Norway and USA. Two oil-producing countries in South East Asia, Malaysia and Thailand are also reviewed to identify potential gaps in decommissioning legislation for countries in its infancy in decommissioning. The differences were identified in terms of decommissioning preparation, decommissioning technical execution, additional environmental requirements and financial security framework. In conclusion, the majority of the regulations covering the technical section are similar within all countries studied. Major differences lie in two overarching philosophies of the framework – a prescriptive regime versus a goal-setting regime. Other decommissioning aspects appear to attract increasing attention, such as in expanding clarity on in situ decommissioning, residual liabilities, optimising finance related issues of decommissioning and offshore to onshore waste movement. These gaps in the existing framework can be filled by taking an evidence-based stand in developing the framework.

Neuroscience Based Design: Fundamentals and Applications

Neuroscience-based or neuroscience-informed design is a new application area of Brain-Computer Interaction (BCI). It takes its roots in study of human well-being in architecture, human factors study in engineering and manufacturing including neuroergonomics. In traditional human factors studies and/or well-being study, mental workload, stress, and emotion are obtained through questionnaires that are administered upon completion of some task and/or the whole experiment. Recent advances in BCI research allow for using Electroencephalogram (EEG) based brain state recognition algorithms to assess the interaction between brain and human performance. We propose and develop an EEG-based system CogniMeter to monitor and analyze human factors measurements of newly designed software/hardware systems and/or working places. Machine learning techniques are applied to the EEG data to recognize levels of mental workload, stress and emotions during each task. The EEG is used as a tool to monitor and record the brain states of subjects during human factors study experiments. We describe two applications of CogniMeter system: human performance assessment in maritime simulator and EEG-based human factors evaluation in Air Traffic Control (ATC) workplace. By utilizing the proposed EEG-based system, true understanding of subjects working patterns can be obtained. Based on the analyses of the objective real time EEG-based data together with the subjective feedback from the subjects, we are able to reliably evaluate current systems/hardware and/or working place design and refine new concepts and design of future systems.

Seakeeping analysis of a modern AHTS vessel for operation in Brazilian offshore waters

The paper presents results of a study on the seakeeping performance of a modern Anchor Handling Tug Supply (AHTS) vessel. It assesses the capability of the vessel to operate safely and efficiently in typical open sea conditions, characteristic of the South Atlantic (Brazil). The RAOs for various wave headings, speeds and loading conditions are calculated using the well-established seakeeping 3D panel code NEWDRIFT developed at NTUA-SDL. The vessels responses for two typical South Atlantic wave spectra are calculated, analyzed and assessed.