Trends, relationship, and model of selected service sector workers in Malaysia: Physiological responses of mental workload and mental fatigue during performing real-time tasks
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Summary
This study addresses the lack of empirical data and predictive models regarding mental workload and mental fatigue among service sector workers in Malaysia. As the Malaysian service industry expands, workers face increased occupational risks, with human error cited as a primary cause of accidents. The research aims to identify trends and relationships between mental workload and fatigue levels during real-time tasks and to develop conceptual models for predicting these states. The study focuses on office workers in government agencies, a group exposed to high mental demands through human-machine interactions. The experimental design involved ten participants with a mean age of 35 years and at least five years of work experience. Participants performed two main tasks: data entry (Task 1) and arithmetic calculations (Task 2), each lasting one hour. The experiment was divided into two segments: Without Rest (WoR) and With Rest (WR). Physiological data were collected using Electroencephalogram (EEG) to measure brain activity (Theta, Alpha, and Beta bands), Electrooculogram (EOG) to remove blink artifacts, and an Actiheart device to monitor heart rate (HR). Task performance was measured by accuracy and efficiency. Statistical analysis included repeated measures ANOVA to assess differences across tasks and time-on-task, Pearson correlation to determine relationships between variables, and multiple linear regression to develop predictive models. The results indicated significant variations in physiological responses based on task type and rest conditions. EEG analysis revealed that Alpha signal power was significantly higher at the end of the WR segment compared to the WoR segment (p<0.05), suggesting a change in mental state due to rest. Heart rate measurements showed that HR during WR tasks was significantly lower than during WoR tasks across all activities (p<0.05). Specific EEG channels, such as P3P4 and O1O2, demonstrated significant effects of task type and time-on-task on Theta and Beta relative powers, indicating that different tasks induced varying levels of mental workload. For instance, Task 1a induced less mental workload than Task 1c. The study successfully developed seven conceptual models with strong variable correlations (r>0.05) to evaluate the variability of mental workload and fatigue during data entry and arithmetic tasks. The significance of this research lies in its provision of validated parameters—specifically brain signals and heart rate monitoring—alongside task performance measures, for assessing mental workload and fatigue. The findings offer a reference for organizations to optimize resource planning and job design by managing mental workload conditions. By understanding the physiological trends associated with fatigue, employers can implement strategies to minimize mental fatigue occurrence, thereby reducing the risk of human error and occupational accidents in the service sector. The developed models serve as a foundational tool for future interventions aimed at enhancing worker safety and productivity in high-demand environments.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | cached | — | — | 124 | 2026-08-10 |
| clean | success | clean | — | — | 1 | 2026-08-09 |
| chunk | success | chunk | — | — | 1 | 2026-08-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-08-09 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 123 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 11 | 2026-08-11 |
| verify | success | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.
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- Empirical Findings: physiological data, self report data
- Theoretical Contribution: theory or model