RESUMEN
OBJECTIVE: This study aims to reconstruct a real-world Crash Injury Research and Engineering Network vehicle-to-pedestrian impact to supplement the determination of pedestrian kinematics and injury causation. METHODS: A case involving a 46-year-old male pedestrian with a height of 163 cm and mass of 100 kg that was impacted by a 2019 Dodge Charger Pursuit police cruiser at an approximate velocity of 20.1 m/s was reconstructed. The case vehicle was represented by a rigid shell of a 2019 Dodge Charger vehicle exterior from an open-source database. The case pedestrian was represented by the Global Human Body Models Consortium (GHBMC) 50th percentile male simplified pedestrian human body model. The GHBMC model was isometrically scaled to a height of 163 cm and the external layer of flesh was morphed to a male reference geometry with the same age, height, and body mass index as the case pedestrian. The approximate location and position of the pedestrian at the time of impact was determined from case vehicle dashboard camera images and the pedestrian model was adjusted accordingly. RESULTS: Reconstruction kinematics aligned with proposed CIREN case kinematics. The GHBMC model predicted fractures of the left inferior ischiopubic ramus, superior pubic ramus, ilium, sacral ala, acetabulum, and right ilium. CONCLUSIONS: Finite element reconstructions of real-world pedestrian impacts are useful for analyzing pedestrian kinematics and provide an effective tool for improving pedestrian impact injury analyses.
Asunto(s)
Accidentes de Tránsito/estadística & datos numéricos , Análisis de Elementos Finitos , Peatones/estadística & datos numéricos , Fenómenos Biomecánicos , Fracturas Óseas/epidemiología , Cuerpo Humano , Humanos , Masculino , Persona de Mediana Edad , Modelos BiológicosRESUMEN
OBJECTIVE: Area under the receiver operating characteristic (AROC) is commonly used to evaluate an injury metric's ability to discriminate between injury and noninjury cases. However, AROC has limitations and may not handle censored data sets adequately. Survival methodology creates robust estimates of injury risk curves (IRCs) which accommodate censored data. We developed an observation-adjusted ROC (oaROC), an AROC-like statistic calculated from the IRC. METHODS: oaROC uses an observational distribution and an IRC to measure true positive rate (TPR) and false positive rate (FPR). The oaROC represents what the AROC would be with a large number of observations sampled from the IRC. We verified this using a limit test with simulated data sets at various sample sizes drawn from an assumed "true" IRC. For each sample size, 5,000 different data sets were created; a conventional AROC was calculated for each data set and compared with the single oaROC, which was calculated from the "true" IRC and not dependent on sample size. RESULTS: The oaROC, calculated from the simulated IRC, was 0.911. At a sample size of 20, the mean AROC was 0.930 (2.0% difference). At a sample size of 1,000, the mean AROC was 0.9114 (0.02% difference). CONCLUSION: We verified that AROC approaches the oaROC with increasing sample sizes, and oaROC presents a measure of IRC discriminatory ability. Survival methodology can estimate IRCs using censored observations and the oaROC was designed with this in mind. The oaROC may be a useful measure of discrimination for data sets containing censored data. Further investigation is needed to evaluate oaROC calculated from estimated IRCs.
Asunto(s)
Accidentes de Tránsito/estadística & datos numéricos , Curva ROC , Heridas y Lesiones/epidemiología , Fenómenos Biomecánicos , Humanos , Medición de Riesgo/métodosRESUMEN
Pedestrians represent one of the most vulnerable road users and comprise nearly 22% the road crash-related fatalities in the world. Therefore, protection of pedestrians in car-to-pedestrian collisions (CPC) has recently generated increased attention with regulations involving three subsystem tests. The development of a finite element (FE) pedestrian model could provide a complementary component that characterizes the whole-body response of vehicle-pedestrian interactions and assesses the pedestrian injuries. The main goal of this study was to develop and to validate a simplified full body FE model corresponding to a 50th male pedestrian in standing posture (M50-PS). The FE model mesh and defined material properties are based on a 50th percentile male occupant model. The lower limb-pelvis and lumbar spine regions of the human model were validated against the postmortem human surrogate (PMHS) test data recorded in four-point lateral knee bending tests, pelvic\abdomen\shoulder\thoracic impact tests, and lumbar spine bending tests. Then, a pedestrian-to-vehicle impact simulation was performed using the whole pedestrian model, and the results were compared to corresponding PMHS tests. Overall, the simulation results showed that lower leg response is mostly within the boundaries of PMHS corridors. In addition, the model shows the capability to predict the most common lower extremity injuries observed in pedestrian accidents. Generally, the validated pedestrian model may be used by safety researchers in the design of front ends of new vehicles in order to increase pedestrian protection.
Asunto(s)
Accidentes , Tamaño Corporal , Análisis de Elementos Finitos , Peatones , Adulto , Anciano , Automóviles , Calibración , Femenino , Humanos , Vértebras Lumbares/anatomía & histología , Vértebras Lumbares/fisiología , Masculino , Persona de Mediana Edad , Modelos Anatómicos , Soporte de PesoRESUMEN
The liver is one of the most frequently injured abdominal organs during motor vehicle crashes. Realistic numerical assessments of liver injury risk for the entire occupant population require incorporating inter-subject variations into numerical models. The main objective of this study was to quantify the shape variations of human liver in a seated posture and the statistical distributions of its material properties. Statistical shape analysis was applied to construct shape models of the livers of 15 adult human subjects, recorded in a typical seated (occupant) posture. The principal component analysis was then utilized to obtain the modes of variation, the mean model, and 95% statistical boundary shape models. In addition, a total of 52 tensile tests were performed on the parenchyma of three fresh human livers at four loading rates (0.01, 0.1, 1, and 10 s^-1) to characterize the rate-dependent and failure properties of the human liver. A FE-based optimization approach was employed to identify the material parameters of an Ogden material model for each specimen. The mean material parameters were then determined for each loading rate from the characteristic averages of the stress-strain curves, and a stochastic optimization approach was utilized to determine the standard deviations of the material parameters. Results showed that the first five modes of the human liver shape models account for more than 60% of the overall anatomical variations. The distributions of the material parameters combined with the mean and statistical boundary shape models could be used to develop probabilistic finite element (FE) models, which may help to better understand the variability in biomechanical responses and injuries to the abdominal organs under impact loading.