Physiology-Informed Optimization of Work–Rest Schedules for Construction Workers Using Wrist-Worn Heart-Rate Monitoring

dc.contributor.advisorZahed, Karim
dc.contributor.authorYunis, Tala
dc.contributor.commembersSrour, Issam
dc.contributor.commembersAbou Ibrahim, Hisham
dc.contributor.degreeMEM
dc.contributor.departmentDepartment of Industrial Engineering and Management
dc.contributor.facultyMaroun Semaan Faculty of Engineering and Architecture
dc.contributor.institutionAmerican University of Beirut
dc.date2025
dc.date.accessioned2026-01-14T09:39:21Z
dc.date.submitted2026-01-12T22:00:00Z
dc.descriptionRelease date: 2029-01-13.
dc.description.abstractIn 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.urihttps://hdl.handle.net/10938/35127
dc.language.isoen
dc.subject.lcshConstruction workers --Health and hygiene
dc.subject.lcshConstruction industry--Employees
dc.subject.lcshFatigue
dc.subject.lcshHeart rate monitoring
dc.subject.lcshMathematical optimization
dc.subject.lcshWearable technology
dc.subject.lcshRest periods
dc.titlePhysiology-Informed Optimization of Work–Rest Schedules for Construction Workers Using Wrist-Worn Heart-Rate Monitoring
dc.typeThesis
local.AUBID202472161

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