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Data · dataset · 2025

Human Motion Data in Complex Construction Environments Setup with and without Knee Exoskeleton Assistance

Listed in Teesside University Research Data Repository

Construction work involves complex, non-repetitive tasks that increase risks of work-related musculoskeletal disorders (WMSDs) and productivity loss.

Description

This study presents an integrated evaluation framework combining wearable knee exoskeleton assistance, immersive virtual reality (VR) task scenarios, and synchronized multi-sensor measurements to quantify safety- and performance-related outcomes in construction-like settings.

Using a modular stair–ramp–deck platform, twenty-one adults completed multi-task protocols with and without knee exoskeleton assistance in a randomized crossover design while the motion capture system, force plates, electromyography (EMG), inertial measurement units (IMUs), and metabolic sensing recorded biomechanics, stability, and effort. Assistance reduced lower-limb muscular demand and improved postural stability during kneeling and VR precision tasks.

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User surveys indicated perceived stability gains but highlighted comfort and weight concerns. The framework enables task-relevant, reproducible assessment of safety and productivity in realistic construction environments. All multimodal data and protocols are released to support benchmarking and future task-aware assistance systems.

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Teesside University Research Data Repositoryoai:data.mendeley.com/rygyy8mdhp.115 h agoJSON v1
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concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
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publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title