Sex, Age and Stature Affects Neck Biomechanical Responses in Frontal and Rear Impacts Assessed Using Finite Element Head and Neck Models
Bibliographic record
Abstract
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 (F0575YO) and a 50th percentile male aged neck model (M5075YO) were developed from existing young (F0526YO and M5026YO) 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 M5075YO model predicted hard tissue failure, attributed to the combined effect of the more anteriorly located head with age, when compared to the M5026YO, and greater neck length relative to the female models. In the rear impacts, the F0575YO model predicted higher relative facet joint shear compared to the F0526YO, and higher relative facet joint rotation and nominal intervertebral disc strain compared to the M5075YO. When comparing the male models, the relative facet joint kinematics predicted by the M5026YO and M5075YO 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".