Citation
Abstract
Service sector is a job that is considered exposed to high mental demand. There is lack of technique to measure issues related to the mental workload and mental fatigue levels among workers. Moreover, no studies have yet developed a model to predict mental fatigue especially for service sector workers. It is necessary to investigate mental workload and mental fatigue in real time working activities. The main purpose of this study was to identify the trends and relationship between mental workload and mental fatigue level among service sector workers. Ten participants with a mean age of 35.00±8.62 (SD) years took part in the study. Two experiments in Without Rest (WoR) and With Rest (WR) segments involving data entry and arithmetic tasks were conducted. Physiological measures using Electroencephalogram (EEG), Electrooculogram (EOG) and heart rate (HR) were assessed while participants were performing the tasks. The result shows that EEG alpha signal was significantly higher at the end of WR compared to WoR segment (p<0.05). Comparison between WoR and WR segments for each task show that HR of WR tasks were significantly lower in all tasks (p<0.05). This study developed seven mental workload and mental fatigue conceptual models with strong variables correlations (r>0.05) to evaluate the variability of both parts of two types of activities, namely, data entry and arithmetic tasks. The findings highlighted that validated parameters and methods for mental fatigue and mental workload measures are brain signals and heart rate monitoring, and task performance measure. Significant findings of the study could be as a reference for organizations to plan and manage resources by optimizing mental workload condition and minimizing mental fatigue occurrence.
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Engineering |
Publisher: | Politeknik Negeri Lhokseumawe |
Keywords: | Mental workload; Mental fatigue; Task performance; Service sector; Regression |
Depositing User: | Mohamad Jefri Mohamed Fauzi |
Date Deposited: | 06 Jul 2023 07:05 |
Last Modified: | 06 Jul 2023 07:05 |
URI: | http://psasir.upm.edu.my/id/eprint/102511 |
Statistic Details: | View Download Statistic |
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