Physiology-Informed Optimization of Work–Rest Schedules for Construction Workers Using Wrist-Worn Heart-Rate Monitoring
| dc.contributor.advisor | Zahed, Karim | |
| dc.contributor.author | Yunis, Tala | |
| dc.contributor.commembers | Srour, Issam | |
| dc.contributor.commembers | Abou Ibrahim, Hisham | |
| dc.contributor.degree | MEM | |
| dc.contributor.department | Department of Industrial Engineering and Management | |
| dc.contributor.faculty | Maroun Semaan Faculty of Engineering and Architecture | |
| dc.contributor.institution | American University of Beirut | |
| dc.date | 2025 | |
| dc.date.accessioned | 2026-01-14T09:39:21Z | |
| dc.date.submitted | 2026-01-12T22:00:00Z | |
| dc.description | Release date: 2029-01-13. | |
| dc.description.abstract | In active construction settings, sustained physiological strain contributes to fatigue, injuries, and productivity losses, yet site schedules rarely adapt to workers’ real-time conditions. Most previous studies relied on fixed work–rest periods applied uniformly to all workers, and even when worker-specific scheduling methods were proposed, the physiological inputs were simulated or based on proxy datasets rather than measurements from active sites. Accordingly, this study develops a scheduling approach that uses wrist-based heart-rate reserve (%HRR) to trigger and size breaks, with a mixed-integer linear program (MILP) placing them under daily time and spacing limits, allowing break guidance to update continuously in response to on-site physiological signals. A live %HRR time series from three active sites is passed through a rest-allowance rule that identifies candidate breaks and estimates the recovery benefit of each. A MILP then selects a feasible subset of high-value breaks. In this evaluation, breaks were simulated rather than enforced on-site. The following week’s break schedule is then planned based on the results obtained using three different methods. Results show that 92% of worker-days needed at least one break, with 5−15 min/day being the most common total, and the average required rest ~40 min/day across workers. Under a 30−minute cap, the optimizer retained 84% of candidate breaks, typically by shortening rather than removing them, and reduced window-level mean %HRR by ~8 percentage points compared with no breaks. It also reduced long periods spent at high strain, (≥40% HRR). Field data showed distinct differences between workers and between sites, supporting the need for flexible, physiology-based scheduling. Thus, the approach provides supervisors with a practical way to plan rest windows using field data rather than relying on laboratory or simulation studies. | |
| dc.identifier.uri | https://hdl.handle.net/10938/35127 | |
| dc.language.iso | en | |
| dc.subject.lcsh | Construction workers --Health and hygiene | |
| dc.subject.lcsh | Construction industry--Employees | |
| dc.subject.lcsh | Fatigue | |
| dc.subject.lcsh | Heart rate monitoring | |
| dc.subject.lcsh | Mathematical optimization | |
| dc.subject.lcsh | Wearable technology | |
| dc.subject.lcsh | Rest periods | |
| dc.title | Physiology-Informed Optimization of Work–Rest Schedules for Construction Workers Using Wrist-Worn Heart-Rate Monitoring | |
| dc.type | Thesis | |
| local.AUBID | 202472161 |
Files
Original bundle
1 - 3 of 3
Loading...
- Name:
- YunisTala_2026.pdf
- Size:
- 1.31 MB
- Format:
- Adobe Portable Document Format
- Description:
- Main Thesis
Loading...
- Name:
- YunisTala_ReleaseForm_2026.pdf
- Size:
- 582.66 KB
- Format:
- Adobe Portable Document Format
- Description:
- Release Form
Loading...
- Name:
- YunisTala_ApprovalForm_2026.pdf
- Size:
- 3.97 MB
- Format:
- Adobe Portable Document Format
- Description:
- Approval Form
License bundle
1 - 1 of 1
Loading...
- Name:
- license.txt
- Size:
- 1.65 KB
- Format:
- Item-specific license agreed upon to submission
- Description: