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Prediction of Neural Space Narrowing and Soft Tissue Injury of the Cervical Spine Concerning Head Restraint Arrangements in Traffic Collisions
- Source :
- Applied Sciences, Vol 11, Iss 1, p 145 (2020)
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- Common quantitative assessments of neck injury criteria do not predict anatomical neck injuries and lack direct relations to design parameters of whiplash-protection systems. This study aims to provide insights into potential soft tissue-level injury sites based on the interactions developed in-between different anatomical structures in case of a rear-end collision. A detailed finite element human model has exhibited an excellent biofidelity when validated against volunteer impacts. Three head restraint arrangements were simulated, predicting both the kinematic response and the anatomical pain source at each arrangement. Head restraint’s contribution has reduced neck shear and head kinematics by at least 70 percent, minimized pressure gradients acting on ganglia and nerve roots less than half. Posterior column ligaments were the most load-bearing components, followed by the lower intervertebral discs and upper capsular ligaments. Sprain of the interspinous ligamentum flavum at early stages has caused instability in the craniovertebral structure causing its discs and facet joints to be elevated compressive loads. Excessive hyperextension motion, which occurred in the absence of the head restraint, has promoted a stable avulsion teardrop fracture of the fourth vertebral body’s anteroinferior aspect and rupture the anterior longitudinal ligament. The observed neck injuries can be mathematically related to head–torso relative kinematics. These relations will lead to the development of a comprehensive neck injury criterion that can predict the injury level. This, in turn, will impose a significant impact on the design processes of vehicle anti-whiplash safety equipment.
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 11
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Applied Sciences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.269953d385c944f99d8eb1c66cf1d3ae
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/app11010145