Relating Real-World Falls to Laboratory Test Conditions

Abstract Purpose Falls account for over half of fatal work-related traumatic brain injuries, yet current safety helmet standards do not test energy levels representative of falls. Additionally, little is known about how fall impact mitigating mechanisms (FIMMs), such as fall arrest movements and/or object contact, and reduce head impact velocity. This study used a multi-step analytical approach to estimate head impact speeds from various fall heights while factoring in energy reduction due to FIMMs. Methods Laboratory drop tests established peak linear accelerations (PLAs) and head injury criterion (HIC) values across a range of impact velocities. These PLA/HIC values were then input into skull fracture risk curves to establish the risk of skull fracture at various head impact speeds. At matched levels of risk, a risk curve relating real-world fall height to skull fracture risk was used to estimate the fall heights associated with different head impact velocities. A worst-case head impact velocity representing a direct, head-first fall without FIMMs was calculated using basic energy assumptions from the specified fall height. FIMMs were quantified as the percent reduction in the worst-case velocity from a given fall height to the laboratory head impact velocity. Results FIMMs may reduce head impact velocity by 44.5–64.4% compared to a head-first impact without FIMMs. Conclusion To evaluate safety helmets under realistic impact conditions, lab-based head impact velocities should be reduced by 44.5–64.4% from the worst-case velocity to account for a population-level estimate energy reduction associated with FIMMs.

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Publication Details

Journal
Annals of Biomedical Engineering
Published
2026-09-30
DOI
https://doi.org/10.1007/s10439-026-04353-w
Primary Topic
Automotive and Human Injury Biomechanics
Type
article
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article

Relating Real-World Falls to Laboratory Test Conditions

Nicole E.‐P. Stark, Michael L. Madigan, Susanna M Gagliardi, Steve Rowson
Annals of Biomedical Engineering
Automotive and Human Injury Biomechanics
article

Relating Real-World Falls to Laboratory Test Conditions

Nicole E.‐P. Stark, Michael L. Madigan, Susanna M Gagliardi, Steve Rowson
article en

Abstract

Abstract Purpose Falls account for over half of fatal work-related traumatic brain injuries, yet current safety helmet standards do not test energy levels representative of falls. Additionally, little is known about how fall impact mitigating mechanisms (FIMMs), such as fall arrest movements and/or object contact, and reduce head impact velocity. This study used a multi-step analytical approach to estimate head impact speeds from various fall heights while factoring in energy reduction due to FIMMs. Methods Laboratory drop tests established peak linear accelerations (PLAs) and head injury criterion (HIC) values across a range of impact velocities. These PLA/HIC values were then input into skull fracture risk curves to establish the risk of skull fracture at various head impact speeds. At matched levels of risk, a risk curve relating real-world fall height to skull fracture risk was used to estimate the fall heights associated with different head impact velocities. A worst-case head impact velocity representing a direct, head-first fall without FIMMs was calculated using basic energy assumptions from the specified fall height. FIMMs were quantified as the percent reduction in the worst-case velocity from a given fall height to the laboratory head impact velocity. Results FIMMs may reduce head impact velocity by 44.5–64.4% compared to a head-first impact without FIMMs. Conclusion To evaluate safety helmets under realistic impact conditions, lab-based head impact velocities should be reduced by 44.5–64.4% from the worst-case velocity to account for a population-level estimate energy reduction associated with FIMMs.

Annals of Biomedical Engineering
Virginia Tech (US)
Affordable and clean energy
Openalex Percentile: Top 12%
Automotive and Human Injury Biomechanics
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Relating Real-World Falls to Laboratory Test Conditions — Nicole E.‐P. Stark, Michael L. Madigan, et al. · Annals of Biomedical Engineering (2026) | TGRS Research Map | TGRS