Is optimized restraint system for an occupant with obesity different than that for a normal BMI occupant?

OBJECTIVE: To optimize the components of restraint systems for protecting obese (BMI = 35 kg/m2) and normal BMI (BMI = 25) human body models (HBMs) in frontal crash simulations, and to compare the two optimized designs. METHODS: The Life Years Lost metric, which incorporates the risk of injury and long-term disability to different body regions, was used as the optimization objective function. Parametric simulations, sampled from a 15-parameter design space using the Latin Hypercube technique, were performed and metamodels of the HBM responses were developed. A genetic algorithm was applied to the metamodels to identify the optimized designs. RESULTS: While most of the restraint parameters between the optimized design for obese and normal BMI HBMs were similar, the main difference was that the restraint for the obese HBM included an under-the-seat airbag, which mitigated its lower extremity excursion, improved its torso kinematics, and decreased its lower extremity and lumbar spine injury risks. The optimized designs for both HBMs included an inflatable seat belt, which reduced the risk of thoracic injury. CONCLUSIONS: The design recommendations from this study should be considered to improve safety of occupants with obesity.

Leveraging machine learning for predicting human body model response in restraint design simulations.

The objective of this study was to leverage and compare multiple machine learning techniques for predicting the human body model response in restraint design simulations. Parametric simulations with 16 independent variables were performed. Ordinary least-squares (OLS), least absolute shrinkage and selection operator (LASSO), neural network (NN), support vector regression (SVR), regression forest (RF), and an ensemble method were used to develop response surface models of the simulations. The hyperparameters of the machine learning techniques were optimized through grid search and cross-validation to avoid under-fitting and over-fitting. The ensemble method outperformed other techniques, followed by LASSO, SVR, NN, RF, and OLS. Findings indicated that optimizing the metamodel hyper-parameters are essential to predict the optimum set of restraint design parameters.

Comparison of injuries of belted occupants among different BMI categories in frontal crashes.

BACKGROUND: Previous studies have shown that occupants with obesity are at a greater risk of fatality and serious injury than other occupants in motor vehicle crashes. OBJECTIVE: To provide a more complete description of the most frequent injuries and the most frequently injured body regions for occupants with obesity. METHODS: Sampled cases (n = 13,470) representing ~4.7 million adult occupants involved in frontal crashes (between 2000 and 2015) were selected from the U.S. National Automotive Sampling System-Crashworthiness Data System database. A retrospective cohort study was performed to study the effect of BMI on the risk of injury to different body regions and to identify the most frequent injuries to occupants with different BMIs. Lastly, in-depth crash analysis cases from the U.S. Crash Injury Research and Engineering Network (CIREN) database were studied to elucidate the source of the most common injuries to occupants with obesity. RESULTS: Occupants with obesity experienced a higher risk of upper extremity (4.79 vs 2.92%), lower extremity (8.37 vs 3.23%), and spine (1.53 vs 1.09%) injuries than other occupants. After adjusting for other variables, the risks of spinal, thoracic, and extremities injuries were found to be affected by the BMI class. Seven out of the ten most common injuries sustained by occupants with obesity were lower extremity injuries, and talus fractures were the most common overall. Direct loading through the plantar surface of the foot by the vehicle toe pan was found to be a likely cause of many of those injuries based on CIREN cases. CONCLUSIONS: The injuries of occupants with obesity are different than other occupants which can be attributed to their different interaction with the seat belt and vehicle interior. The findings of this study should be considered for designing restraint systems to protect occupants with obesity in car crashes.

Relative Motion Between the Helmet and the Head in Football Impact Test.

Approximately 1.6-3.8 million sports-related traumatic brain injuries occur each year in the U.S. Researchers track the head motion using a variety of techniques to study the head injury biomechanics. To understand how helmets provide head protection, quantification of the relative motion between the head and the helmet is necessary. The purpose of this study was to compare helmet and head kinematics and quantify the relative motion of helmet with respect to head during experimental representations of on-field American football impact scenarios. Seven helmet-to-helmet impact configurations were simulated by propelling helmeted crash test dummies into each other. Head and helmet kinematics were measured with instrumentation and an optical motion capture system. The analysis of results, from 10 ms prior to the helmet contact to 20 ms after the loss of helmet contact, showed that the helmets translated 12-41 mm and rotated up to 37 deg with respect to the head. The peak resultant linear acceleration of the helmet was about 2-5 times higher than the head. The peak resultant angular velocity of the helmet ranged from 37% less to 71% more than the head, depending on the impact conditions. The results of this study demonstrate that the kinematics of the head and the helmet are noticeably different and that the helmet rotates significantly with respect to the head during impacts. Therefore, capturing the helmet kinematics using a video motion tracking methodology is not sufficient to study the biomechanics of the head. Head motion must be measured independently of the helmet.

Skin mechanical properties and modeling: A review.

The mechanical properties of the skin are important for various applications. Numerous tests have been conducted to characterize the mechanical behavior of this tissue, and this article presents a review on different experimental methods used. A discussion on the general mechanical behavior of the skin, including nonlinearity, viscoelasticity, anisotropy, loading history dependency, failure properties, and aging effects, is presented. Finally, commonly used constitutive models for simulating the mechanical response of skin are discussed in the context of representing the empirically observed behavior.

Assessment of model-based image-matching for future reconstruction of unhelmeted sport head impact kinematics.

Player-to-player contact inherent in many unhelmeted sports means that head impacts are a frequent occurrence. Model-Based Image-Matching (MBIM) provides a technique for the assessment of three-dimensional linear and rotational motion patterns from multiple camera views of a head impact event, but the accuracy is unknown for this application. The goal of this study is to assess the accuracy of the MBIM method relative to reflective marker-based motion analysis data for estimating six degree of freedom head displacements and velocities in a staged pedestrian impact scenario at 40 km/h. Results showed RMS error was under 20 mm for all linear head displacements and 0.01-0.04 rad for head rotations. For velocities, the MBIM method yielded RMS errors between 0.42 and 1.29 m/s for head linear velocities and 3.53-5.38 rad/s for angular velocities. This method is thus beneficial as a tool to directly measure six degree of freedom head positional data from video of sporting head impacts, but velocity data is less reliable. MBIM data, combined in future with velocity/acceleration data from wearable sensors could be used to provide input conditions and evaluate the outputs of multibody and finite element head models for brain injury assessment of sporting head impacts.

Development of a Single-Degree-of-Freedom Mechanical Model for Predicting Strain-Based Brain Injury Responses.

Linking head kinematics to injury risk has been the focus of numerous brain injury criteria. Although many early forms were developed using mechanics principles, recent criteria have been developed using empirical methods based on subsets of head impact data. In this study, a single-degree-of-freedom (sDOF) mechanical analog was developed to parametrically investigate the link between rotational head kinematics and brain deformation. Model efficacy was assessed by comparing the maximum magnitude of displacement to strain-based brain injury predictors from finite element (FE) human head models. A series of idealized rotational pulses covering a broad range of acceleration and velocity magnitudes (0.1-15 krad/s2 and 1-100 rad/s) with durations between 1 and 3000 ms were applied to the mechanical models about each axis of the head. Results show that brain deformation magnitude is governed by three categories of rotational head motion each distinguished by the duration of the pulse relative to the brain's natural period: for short-duration pulses, maximum brain deformation depended primarily on angular velocity magnitude; for long-duration pulses, brain deformation depended primarily on angular acceleration magnitude; and for pulses relatively close to the natural period, brain deformation depended on both velocity and acceleration magnitudes. These results suggest that brain deformation mechanics can be adequately explained by simple mechanical systems, since FE model responses and experimental brain injury tolerances exhibited similar patterns to the sDOF model. Finally, the sDOF model was the best correlate to strain-based responses and highlighted fundamental limitations with existing rotational-based brain injury metrics.

Scaling approach in predicting the seatbelt loading and kinematics of vulnerable occupants: How far can we go?

OBJECTIVE: Occupants with extreme body size and shape, such as the small female or the obese, were reported to sustain high risk of injury in motor vehicle crashes (MVCs). Dimensional scaling approaches are widely used in injury biomechanics research based on the assumption of geometrical similarity. However, its application scope has not been quantified ever since. The objective of this study is to demonstrate the valid range of scaling approaches in predicting the impact response of the occupants with focus on the vulnerable populations. METHODS: The present analysis was based on a data set consisting of 60 previously reported frontal crash tests in the same sled buck representing a typical mid-size passenger car. The tests included two categories of human surrogates: 9 postmortem human surrogates (PMHS) of different anthropometries (stature range: 147-189 cm; weight range: 27-151 kg) and 5 anthropomorphic test devices (ATDs). The impact response was considered including the restraint loads and the kinematics of multiple body segments. For each category of the human surrogates, a mid-size occupant was selected as a baseline and the impact response was scaled specifically to another subject based on either the body mass (body shape) or stature (the overall body size). To identify the valid range of the scaling approach, the scaled response was compared to the experimental results using assessment scores on the peak value, peak timing (the time when the peak value occurred), and the overall curve shape ranging from 0 (extremely poor) to 1 (perfect match). Scores of 0.7 to 0.8 and 0.8 to 1.0 indicate fair and acceptable prediction. RESULTS: For both ATDs and PMHS, the scaling factor derived from body mass proved an overall good predictor of the peak timing for the shoulder belt (0.868, 0.829) and the lap belt (0.858, 0.774) and for the peak value of the lap belt force (0.796, 0.869). Scaled kinematics based on body stature provided fair or acceptable prediction on the overall head/shoulder kinematics (0.741, 0.822 for the head; 0.817, 0.728 for the shoulder) regardless of the anthropometry. The scaling approach exhibited poor prediction capability on the curve shape for the restraint force (0.494 and 0.546 for the shoulder belt; 0.585 and 0.530 for the lap belt). It also cannot well predict the excursion of the pelvis and the knee. CONCLUSIONS: The results revealed that for the peak lap belt force and the forward motion of the head and shoulder, the underlying linear relationship with body size and shape is valid over a wide anthropometric range. The chaotic nature of the dynamic response cannot be fully recovered by the assumption of the whole-body geometrical similarity, especially for the curve shape. The valid range of the scaling approach established in this study can be reasonably referenced in predicting the impact response of a given specific population with expected deviation. Application of this knowledge also includes proposing strategies for restraint configuration and providing reference for ATD and/or human body model (HBM) development for vulnerable occupants.