An investigation of dimensional scaling using cervical spine motion segment finite element models

Methodology to geometrically age human body models to average and subject-specific anthropometrics, demonstrated using a small stature female model assessed in a side impact

The aged population has been associated with an increased risk of injury in car-crash, creating a critical need for improved assessment of safety systems. Finite element human body models (HBMs) have been proposed, but require representative geometry of the aged population and high mesh quality. A new hybrid Morphing-CAD methodology was applied to a 26-year-old (YO) 5^th percentile female model to create average 75YO and subject-specific 86YO HBMs. The method achieved accurate morphing targets while retaining high mesh quality. The three HBMs were integrated into a side sled impact test demonstrating similar kinematic response but differing rib fracture patterns.

Sex, Age and Stature Affects Neck Biomechanical Responses in Frontal and Rear Impacts Assessed Using Finite Element Head and Neck Models

The increased incidence of injury demonstrated in epidemiological data for the elderly population, and females compared to males, has not been fully understood in the context of the biomechanical response to impact. A contributing factor to these differences in injury risk could be the variation in geometry between young and aged persons and between males and females. In this study, a new methodology, coupling a CAD and a repositioning software, was developed to reposture an existing Finite element neck while retaining a high level of mesh quality. A 5th percentile female aged neck model (F05_75YO) and a 50th percentile male aged neck model (M50_75YO) were developed from existing young (F05_26YO and M50_26YO) neck models (Global Human Body Models Consortium v5.1). The aged neck models included an increased cervical lordosis and an increase in the facet joint angles, as reported in the literature. The young and the aged models were simulated in frontal (2, 8, and 15 g) and rear (3, 7, and 10 g) impacts. The responses were compared using head and relative facet joint kinematics, and nominal intervertebral disc shear strain. In general, the aged models predicted higher tissue deformations, although the head kinematics were similar for all models. In the frontal impact, only the M50_75YO model predicted hard tissue failure, attributed to the combined effect of the more anteriorly located head with age, when compared to the M50_26YO, and greater neck length relative to the female models. In the rear impacts, the F05_75YO model predicted higher relative facet joint shear compared to the F05_26YO, and higher relative facet joint rotation and nominal intervertebral disc strain compared to the M50_75YO. When comparing the male models, the relative facet joint kinematics predicted by the M50_26YO and M50_75YO were similar. The contrast in response between the male and female models in the rear impacts was attributed to the higher lordosis and facet angle in females compared to males. Epidemiological data reported that females were more likely to sustain Whiplash Associated Disorders in rear impacts compared to males, and that injury risk increases with age, in agreement with the findings in the present study. This study demonstrated that, although the increased lordosis and facet angle did not affect the head kinematics, changes at the tissue level were considerable (e.g., 26% higher relative facet shear in the female neck compared to the male, for rear impact) and relatable to the epidemiology. Future work will investigate tissue damage and failure through the incorporation of aged material properties and muscle activation.

Multilevel Validation of a Male Neck Finite Element Model With Active Musculature

Computational models of the human neck have been developed to assess human response in impact scenarios; however, the assessment and validation of such models is often limited to a small number of experimental data sets despite being used to evaluate the efficacy of safety systems and potential for injury risk in motor vehicle collisions. In this study, a full neck model (NM) with active musculature was developed from previously validated motion segment models of the cervical spine. Tissue mechanical properties were implemented from experimental studies, and were not calibrated. The neck model was assessed with experimental studies at three levels of increasing complexity: ligamentous cervical spine in axial rotation, axial tension, frontal impact, and rear impact; postmortem human subject (PMHS) rear sled impact; and human volunteer frontal and lateral sled tests using an open-loop muscle control strategy. The neck model demonstrated good correlation with the experiments ranging from quasi-static to dynamic, assessed using kinematics, kinetics, and tissue-level response. The contributions of soft tissues, neck curvature, and muscle activation were associated with higher stiffness neck response, particularly for low severity frontal impact. Experiments presenting single-value data limited assessment of the model, while complete load history data and cross-correlation enabled improved evaluation of the model over the full loading history. Tissue-level metrics demonstrated higher variability and therefore lower correlation relative to gross kinematics, and also demonstrated a dependence on the local tissue geometry. Thus, it is critical to assess models at the gross kinematic and the tissue levels.

Variations in User Implementation of the CORA Rating Metric

The CORA rating metric is frequently used in the field of injury biomechanics to compare the similarity of response time histories. However, subjectivity exists within the CORA metric in the form of user-customizable parameters that give the metric the flexibility to be used for a variety of applications. How these parameters are customized is not always reported in the literature, and it is unknown how these customizations affect the CORA scores. Therefore, the purpose of this study was to evaluate how variations in the CORA parameters affect the resulting similarity scores. A literature review was conducted to determine how the CORA parameters are commonly customized within the literature. Then, CORA scores for two datasets were calculated using the most common parameter customizations and the default parameters. Differences between the CORA scores using customized and default parameters were statistically significant for all customizations. Furthermore, most customizations produced score increases relative to the default settings. The use of standard deviation corridors and exclusion of the corridor component were found to produce the largest score differences. The observed differences demonstrated the need for researchers to exercise transparency when using customized parameters in CORA analyses.