Year: 2026
Type: article
Abstract: PURPOSE: Falls and trips are a leading cause of work-related traumatic brain injuries, yet the protective performance of industrial helmets in such scenarios remains poorly understood. This study assesses the effectiveness of different industrial helmet designs under impact conditions representative of falls and trips. METHODS: Six industrial helmets with different designs were tested. Four were suspension-based models compliant with EN 397, including two versions of the same model, one with and one without the rotation reduction system, MIPS. Two additional helmets were foam-based, meeting both EN 397 and EN 12492 standards. Helmets were dropped onto angled anvils at different speeds and impact locations to simulate trips and falls. Tests were conducted on two surface types: P80 abrasive papers and roof shingles. The new EN 17950 headform was used. RESULTS: Helmet performance varied by design and impact condition. Foam-based helmets offered better protection against impacts than suspension-based helmets, which showed greater sensitivity to impact location. Front impacts near the rim at 5.5 m/s produced the highest severity, with peak linear accelerations exceeding 700 g for some suspension-based helmets, followed by rear impacts. In the single helmet model evaluated, MIPS reduced peak rotational acceleration. Finally, the influence of the surface type on peak head kinematics was borderline significant, with P80 papers producing larger peak kinematics. CONCLUSION: Helmet design has a key role in protection against trip and fall impacts, with foam-based helmets providing added benefits. These findings highlight the need for improvements in helmet safety standards and helmet designs to better prevent work-related brain injuries.
Source: Annals of Biomedical Engineering
Institutions: Imperial College London, University of Sheffield
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,390
Award: G7371616897
OpenAlex ID: W7128812524