EEG-based assessment in a ship's bridge simulator
Numerous research have attributed the root causes of maritime accidents to be due to performance decrements as a result of unsatisfactory mental cognitive states. Performance decrements includes slower mental processing speed, lowered attention and problem solving capability. Studies have shown that...
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sg-ntu-dr.10356-715132023-03-04T18:24:25Z EEG-based assessment in a ship's bridge simulator Tang, Edwin Lek Wah Ang Hock Eng School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mechanical engineering Numerous research have attributed the root causes of maritime accidents to be due to performance decrements as a result of unsatisfactory mental cognitive states. Performance decrements includes slower mental processing speed, lowered attention and problem solving capability. Studies have shown that mental workload and stress are cognitive states with strong association to performance. If workload or stress levels are too high, performance decreases. Mental workload and stress should therefore be kept under an optimal level, below which an individual can be safely assumed to maintain high performance while carrying out a task. The objective for this project was then to develop an assessment tool to determine whether a trainee "Passes", "Needs Retraining" or "Fails" based on an algorithm that examines if workload or stress levels of that trainee are maintained within specified acceptable threshold levels. "seaTELLar" was the application developed solely for this purpose. In this study, experiments are conducted in Full Mission Bridge Simulators that closely resembles an actual voyage at sea. Emotion, workload and stress levels measured during the simulation exercises were obtained using EEG signals recorded with a high resolution Emotiv Epoc+ headset. This allows for accurate assessments to be made about a trainee's performance. Some key user interfaces of seaTELLar includes smooth scrolling, user friendly choice selection methods, buttons, file uploads, automatic validation of user inputs and graphical representations of the final assessment. Application testing proved that the algorithm used in seaTELLar is capable of returning a reliable assessment to the user. Further operational tests showed that seaTELLar is fully functional and able to meet the objectives for this project. Future works of seaTELLar includes programming the application to support data retrieval from a database and to be more mobile friendly for user convenience. Bachelor of Engineering (Mechanical Engineering) 2017-05-17T06:23:13Z 2017-05-17T06:23:13Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/71513 en Nanyang Technological University 98 p. application/pdf |
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DRNTU::Engineering::Mechanical engineering Tang, Edwin Lek Wah EEG-based assessment in a ship's bridge simulator |
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Numerous research have attributed the root causes of maritime accidents to be due to performance decrements as a result of unsatisfactory mental cognitive states. Performance decrements includes slower mental processing speed, lowered attention and problem solving capability. Studies have shown that mental workload and stress are cognitive states with strong association to performance. If workload or stress levels are too high, performance decreases. Mental workload and stress should therefore be kept under an optimal level, below which an individual can be safely assumed to maintain high performance while carrying out a task. The objective for this project was then to develop an assessment tool to determine whether a trainee "Passes", "Needs Retraining" or "Fails" based on an algorithm that examines if workload or stress levels of that trainee are maintained within specified acceptable threshold levels. "seaTELLar" was the application developed solely for this purpose. In this study, experiments are conducted in Full Mission Bridge Simulators that closely resembles an actual voyage at sea. Emotion, workload and stress levels measured during the simulation exercises were obtained using EEG signals recorded with a high resolution Emotiv Epoc+ headset. This allows for accurate assessments to be made about a trainee's performance. Some key user interfaces of seaTELLar includes smooth scrolling, user friendly choice selection methods, buttons, file uploads, automatic validation of user inputs and graphical representations of the final assessment. Application testing proved that the algorithm used in seaTELLar is capable of returning a reliable assessment to the user. Further operational tests showed that seaTELLar is fully functional and able to meet the objectives for this project. Future works of seaTELLar includes programming the application to support data retrieval from a database and to be more mobile friendly for user convenience. |
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Ang Hock Eng |
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Ang Hock Eng Tang, Edwin Lek Wah |
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Final Year Project |
author |
Tang, Edwin Lek Wah |
author_sort |
Tang, Edwin Lek Wah |
title |
EEG-based assessment in a ship's bridge simulator |
title_short |
EEG-based assessment in a ship's bridge simulator |
title_full |
EEG-based assessment in a ship's bridge simulator |
title_fullStr |
EEG-based assessment in a ship's bridge simulator |
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EEG-based assessment in a ship's bridge simulator |
title_sort |
eeg-based assessment in a ship's bridge simulator |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/71513 |
_version_ |
1759855829016641536 |