EEG-based assessment in a ship's bridge simulator
Maritime accidents are known to have a large impact on the environment, economy, and society. Although safety factor in maritime domain have been reinforced due to the current technology, the rate of accidents has not significantly dropped proportionally. This spike the interest of numerous resea...
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sg-ntu-dr.10356-749582023-03-04T18:23:38Z EEG-based assessment in a ship's bridge simulator Lim, Lip Poong Ang Hock Eng School of Mechanical and Aerospace Engineering DRNTU::Engineering Maritime accidents are known to have a large impact on the environment, economy, and society. Although safety factor in maritime domain have been reinforced due to the current technology, the rate of accidents has not significantly dropped proportionally. This spike the interest of numerous researches to investigate human factor studies in maritime domain. Studies have shown that human factors are the key contribution to the cause of maritime accidents and that performance of individual is highly related to their mental cognitive states. Mental workload and stress levels are the key information that associate human cognition to performance. The objective of this project was to investigate human factors using Electroencephalography(EEG) to monitor the brain state in real time. This partnership with Singapore Polytechnic’s Singapore Maritime Academy(SMA), Nanyang Technological University and Fraunhofer IDM aims to develop an assessment tool which is capable to determine a candidate’s assessment status, “Pass”, “Fail”, or “Retrains” through an algorithm that analyse workload and stress levels against an acceptable threshold level given different difficulty level of tasks. Experiments are conducted on the Bridge simulator during the assessment in realtime. The data retrieval and processing from a database is made simple in this part of the project by a single application before the final assessment tool. Bachelor of Engineering (Mechanical Engineering) 2018-05-25T05:07:57Z 2018-05-25T05:07:57Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/74958 en Nanyang Technological University 68 p. application/pdf |
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DRNTU::Engineering Lim, Lip Poong EEG-based assessment in a ship's bridge simulator |
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Maritime accidents are known to have a large impact on the environment, economy,
and society. Although safety factor in maritime domain have been reinforced due to
the current technology, the rate of accidents has not significantly dropped
proportionally. This spike the interest of numerous researches to investigate human
factor studies in maritime domain. Studies have shown that human factors are the
key contribution to the cause of maritime accidents and that performance of
individual is highly related to their mental cognitive states. Mental workload and
stress levels are the key information that associate human cognition to performance.
The objective of this project was to investigate human factors using
Electroencephalography(EEG) to monitor the brain state in real time. This
partnership with Singapore Polytechnic’s Singapore Maritime Academy(SMA),
Nanyang Technological University and Fraunhofer IDM aims to develop an
assessment tool which is capable to determine a candidate’s assessment status,
“Pass”, “Fail”, or “Retrains” through an algorithm that analyse workload and stress
levels against an acceptable threshold level given different difficulty level of tasks.
Experiments are conducted on the Bridge simulator during the assessment in realtime.
The data retrieval and processing from a database is made simple in this part of
the project by a single application before the final assessment tool. |
author2 |
Ang Hock Eng |
author_facet |
Ang Hock Eng Lim, Lip Poong |
format |
Final Year Project |
author |
Lim, Lip Poong |
author_sort |
Lim, Lip Poong |
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 |
title_full_unstemmed |
EEG-based assessment in a ship's bridge simulator |
title_sort |
eeg-based assessment in a ship's bridge simulator |
publishDate |
2018 |
url |
http://hdl.handle.net/10356/74958 |
_version_ |
1759854715264303104 |