Evaluation of the user/operator fatigue using heart rate with machine learning algorithms

Psychological fatigue has been shown to be highly related to stress and plays a significant part in workplace accidents and mistakes. Therefore, fatigue monitoring can be vital and important for demanding roles, such as those in a high-stress environment. Together with the advancement in Machine Lea...

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Main Author: Hoe, Chang Shen
Other Authors: Chen Chun-Hsien
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/168255
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1682552023-06-10T16:52:51Z Evaluation of the user/operator fatigue using heart rate with machine learning algorithms Hoe, Chang Shen Chen Chun-Hsien School of Mechanical and Aerospace Engineering Fraunhofer Singapore Olga Sourina MCHchen@ntu.edu.sg, eosourina@ntu.edu.sg Engineering::Industrial engineering::Human factors engineering Psychological fatigue has been shown to be highly related to stress and plays a significant part in workplace accidents and mistakes. Therefore, fatigue monitoring can be vital and important for demanding roles, such as those in a high-stress environment. Together with the advancement in Machine Learning and Data Science, techniques can be applied to help recognise and predict levels of human mental workload, stress, fatigue, emotions etc. from biosignals such as Electroencephalogram (EEG), Electrocardiogram (ECG), and eye tracking etc. Such biosignal-based AI systems can be used to properly understand a subject's working routine. The object of this project to is propose a real-time algorithm of fatigue recognition from heart rate based on machine learning techniques for marine port operators. Bachelor of Engineering (Mechanical Engineering) 2023-06-09T07:33:43Z 2023-06-09T07:33:43Z 2023 Final Year Project (FYP) Hoe, C. S. (2023). Evaluation of the user/operator fatigue using heart rate with machine learning algorithms. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/168255 https://hdl.handle.net/10356/168255 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Industrial engineering::Human factors engineering
spellingShingle Engineering::Industrial engineering::Human factors engineering
Hoe, Chang Shen
Evaluation of the user/operator fatigue using heart rate with machine learning algorithms
description Psychological fatigue has been shown to be highly related to stress and plays a significant part in workplace accidents and mistakes. Therefore, fatigue monitoring can be vital and important for demanding roles, such as those in a high-stress environment. Together with the advancement in Machine Learning and Data Science, techniques can be applied to help recognise and predict levels of human mental workload, stress, fatigue, emotions etc. from biosignals such as Electroencephalogram (EEG), Electrocardiogram (ECG), and eye tracking etc. Such biosignal-based AI systems can be used to properly understand a subject's working routine. The object of this project to is propose a real-time algorithm of fatigue recognition from heart rate based on machine learning techniques for marine port operators.
author2 Chen Chun-Hsien
author_facet Chen Chun-Hsien
Hoe, Chang Shen
format Final Year Project
author Hoe, Chang Shen
author_sort Hoe, Chang Shen
title Evaluation of the user/operator fatigue using heart rate with machine learning algorithms
title_short Evaluation of the user/operator fatigue using heart rate with machine learning algorithms
title_full Evaluation of the user/operator fatigue using heart rate with machine learning algorithms
title_fullStr Evaluation of the user/operator fatigue using heart rate with machine learning algorithms
title_full_unstemmed Evaluation of the user/operator fatigue using heart rate with machine learning algorithms
title_sort evaluation of the user/operator fatigue using heart rate with machine learning algorithms
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/168255
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