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A National Survey of Traumatic Brain Injuries Admitted to Hospital in Sweden from 1987 to 2010
Department of Neurosurgery, Karolinska University Hopsital.
KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.ORCID iD: 0000-0002-0980-4051
Department of Epidemiology, National Board of Health and Welfare.
KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.ORCID iD: 0000-0003-0125-0784
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2015 (English)In: Neuroepidemiology, ISSN 0251-5350, E-ISSN 1423-0208Article in journal (Refereed) Accepted
Place, publisher, year, edition, pages
2015.
National Category
Other Medical Sciences
Research subject
Medical Technology
Identifiers
URN: urn:nbn:se:kth:diva-164082OAI: oai:DiVA.org:kth-164082DiVA: diva2:803425
Funder
VINNOVA, IHF 2013-05118
Note

QP 201504

Available from: 2015-04-13 Created: 2015-04-13 Last updated: 2017-12-04Bibliographically approved
In thesis
1. Numerical Accident Reconstructions: A Biomechanical Tool to Understand and Prevent Head Injuries
Open this publication in new window or tab >>Numerical Accident Reconstructions: A Biomechanical Tool to Understand and Prevent Head Injuries
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Traumatic brain injuries (TBIs) are a major health and socioeconomic problem throughout the world, with an estimated 10 million deaths and instances of hospitalization annually. Numerical methods such as finite element (FE) methods can be used to study head injuries and optimize the protection, which can lead to a decrease in the number of injuries. The FE head models were initially evaluated for biofidelity by comparing with donated corpses experiments. However, there are some limitations in experiments of corpses, including material degradation after death. One feasible alternative to evaluating head models with living human tissue is to use reconstruction of real accidents. However, the process of accident reconstruction entails some uncertainties since it is not a controlled experiment. Therefore, a deeper understanding of the accident reconstruction process is needed in order to be able to improve the FE human models. Thus, the aim of this thesis was to evaluate and further develop more advanced strategies for accident reconstructions involving head injuries.

A FE head model was used to study head injuries in accidents. Existing bicycle accident data was used, as were hypothetical accident situations for cyclists and pedestrians. A FE bicycle helmet model having different designs was developed to study the protective effect.

An objective method was developed based on the Overlap Index (OI) and Location Index (LI) to facilitate the comparison of FE model responses with injuries visible in medical images. Three bicycle accident reconstructions were performed and the proposed method evaluated. The method showed to have potential to be an objective method to compare FE model response with medical images and could be a step towards improving the evaluation of results from injury reconstructions.

The simulations demonstrated the protective effect of a bicycle helmet. A decrease was seen in the injurious effect on both the brain tissue and the skull. However, the results also showed that the brain tissue strain could be further decreased by modifying the helmet design.

Two different numerical pedestrian models were compared to evaluate whether the more time-efficient rigid body model could be used, instead of a FE pedestrian model, to roughly determine the initial conditions as an accident reconstruction involves some uncertainties. The difference, in terms of the head impact location, rotation and velocity, attributable to the two models was in the same range as differences due to uncertainties in some of the initial parameters, such as vehicle impact velocity.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. xvi, 88, XIV p.
Series
TRITA-STH : report, ISSN 1653-3836 ; 2015:4
Keyword
Head injuries; Accident Reconstruction; Finite element analysis; Injury prevention; Helmet; Cyclist; Pedestrian; Epidemiology
National Category
Other Medical Sciences
Research subject
Applied Medical Technology
Identifiers
urn:nbn:se:kth:diva-164091 (URN)978-91-7595-512-4 (ISBN)
Public defence
2015-05-08, 3-221, Alfred Nobels Allé 10, Huddinge, 09:00 (English)
Opponent
Supervisors
Note

QC 20150414

Available from: 2015-04-14 Created: 2015-04-13 Last updated: 2015-04-14Bibliographically approved

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Fahlstedt, MadelenKleiven, Svein

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