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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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/168255 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
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