Ranking and Rating Bicycle Helmet Safety Performance in Oblique Impacts Using Eight Different Brain Injury Models.


Journal

Annals of biomedical engineering
ISSN: 1573-9686
Titre abrégé: Ann Biomed Eng
Pays: United States
ID NLM: 0361512

Informations de publication

Date de publication:
Mar 2021
Historique:
received: 29 06 2020
accepted: 01 12 2020
pubmed: 22 1 2021
medline: 27 10 2021
entrez: 21 1 2021
Statut: ppublish

Résumé

Bicycle helmets are shown to offer protection against head injuries. Rating methods and test standards are used to evaluate different helmet designs and safety performance. Both strain-based injury criteria obtained from finite element brain injury models and metrics derived from global kinematic responses can be used to evaluate helmet safety performance. Little is known about how different injury models or injury metrics would rank and rate different helmets. The objective of this study was to determine how eight brain models and eight metrics based on global kinematics rank and rate a large number of bicycle helmets (n=17) subjected to oblique impacts. The results showed that the ranking and rating are influenced by the choice of model and metric. Kendall's tau varied between 0.50 and 0.95 when the ranking was based on maximum principal strain from brain models. One specific helmet was rated as 2-star when using one brain model but as 4-star by another model. This could cause confusion for consumers rather than inform them of the relative safety performance of a helmet. Therefore, we suggest that the biomechanics community should create a norm or recommendation for future ranking and rating methods.

Identifiants

pubmed: 33475893
doi: 10.1007/s10439-020-02703-w
pii: 10.1007/s10439-020-02703-w
pmc: PMC7952345
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1097-1109

Subventions

Organisme : H2020 Marie Skłodowska-Curie Actions ()
ID : 642662
Organisme : H2020 Marie Skłodowska-Curie Actions
ID : 642662
Organisme : NIH HHS
ID : NS092853
Pays : United States
Organisme : NIH HHS
ID : NS092853
Pays : United States
Organisme : NIH HHS
ID : NS092853
Pays : United States

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Auteurs

Madelen Fahlstedt (M)

Division of Neuronic Engineering, KTH Royal Institute of Technology, Hälsovägen 11C, 141 52, Huddinge, Sweden.

Fady Abayazid (F)

Dyson School of Design Engineering, Imperial College London, London, UK.

Matthew B Panzer (MB)

Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, USA.
Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.

Antonia Trotta (A)

School of Mechanical & Materials Engineering, University College Dublin, Belfield, Dublin 4, Ireland.

Wei Zhao (W)

Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, 01605, USA.

Mazdak Ghajari (M)

Dyson School of Design Engineering, Imperial College London, London, UK.

Michael D Gilchrist (MD)

School of Mechanical & Materials Engineering, University College Dublin, Belfield, Dublin 4, Ireland.

Songbai Ji (S)

Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, 01605, USA.
Department of Mechanical Engineering, Worcester Polytechnic Institute, Worcester, MA, 01609, USA.

Svein Kleiven (S)

Division of Neuronic Engineering, KTH Royal Institute of Technology, Hälsovägen 11C, 141 52, Huddinge, Sweden.

Xiaogai Li (X)

Division of Neuronic Engineering, KTH Royal Institute of Technology, Hälsovägen 11C, 141 52, Huddinge, Sweden.

Aisling Ní Annaidh (AN)

School of Mechanical & Materials Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
School of Medicine and Medical Science, University College Dublin, UCD Charles Institute of Dermatology, Belfield, Dublin 4, Ireland.

Peter Halldin (P)

Division of Neuronic Engineering, KTH Royal Institute of Technology, Hälsovägen 11C, 141 52, Huddinge, Sweden. peter.halldin@mipsprotection.com.

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