A First Step Toward a Family of Morphed Human Body Models Enabling Prediction of Population Injury Outcomes.

The injury risk in a vehicle crash can depend on occupant specific factors. Virtual crash testing using finite element human body models (HBMs) to represent occupant variability can enable the development of vehicles with improved safety for all occupants. In this study, it was investigated how many HBMs of different sizes that are needed to represent a population crash outcome through a metamodel. Rib fracture risk was used as an example occupant injury outcome. Morphed HBMs representing variability in sex, height, and weight within defined population ranges were used to calculate population variability in rib fracture risk in a frontal and a side crash. Two regression methods, regularized linear regression with second-order terms and Gaussian process regression (GPR), were used to metamodel rib fracture risk due to occupant variability. By studying metamodel predictive performance as a function of training data, it was found that constructing GPR metamodels using 25 individuals of each sex appears sufficient to model the population rib fracture risk outcome in a general crash scenario. Further, by utilizing the known outcomes in the two crashes, an optimization method selected individuals representative for population outcomes across both crash scenarios. The optimization results showed that 5-7 individuals of each sex were sufficient to create predictive GPR metamodels. The optimization method can be extended for more crashes and vehicles, which can be used to identify a family of HBMs that are generally representative of population injury outcomes in future work.

Personalization of human body models and beyond via image registration.

Finite element human body models (HBMs) are becoming increasingly important numerical tools for traffic safety. Developing a validated and reliable HBM from the start requires integrated efforts and continues to be a challenging task. Mesh morphing is an efficient technique to generate personalized HBMs accounting for individual anatomy once a baseline model has been developed. This study presents a new image registration-based mesh morphing method to generate personalized HBMs. The method is demonstrated by morphing four baseline HBMs (SAFER, THUMS, and VIVA+ in both seated and standing postures) into ten subjects with varying heights, body mass indices (BMIs), and sex. The resulting personalized HBMs show comparable element quality to the baseline models. This method enables the comparison of HBMs by morphing them into the same subject, eliminating geometric differences. The method also shows superior geometry correction capabilities, which facilitates converting a seated HBM to a standing one, combined with additional positioning tools. Furthermore, this method can be extended to personalize other models, and the feasibility of morphing vehicle models has been illustrated. In conclusion, this new image registration-based mesh morphing method allows rapid and robust personalization of HBMs, facilitating personalized simulations.

Head injury criteria assessment using head kinematics from crash tests and accident reconstructions.

OBJECTIVE: The aim of this study was to assess head injury criteria based on their correlation to brain strain in a Finite Element (FE) head model (the KTH Royal Institute of Technology model), by simulation of head kinematics data from frontal and side crash tests with Anthropomorphic Test Devices (ATDs), and from Human Body Model (HBM) accident reconstructions. METHODS: Six Degrees of Freedom (DoF) head kinematic data was extracted from 221 crash tests, consisting of frontal impacts with the THOR-50M ATD, near-side and far-side impacts with the WorldSID-50M ATD, and from 19 FE HBM accident reconstructions. The head injury criteria HIC15, HIP, BrIC, UBrIC, DAMAGE and CIBIC were calculated, and FE head model simulations were conducted using the six DoF kinematics data. The 100th, 99th, and 95th percentile Maximum Principal Strains (MPS) of the brain were extracted and linear regression models with respect to the injury criteria were created. The injury criteria were then evaluated based on the coefficient of determination, R2, and the Normalized Root Mean Square Error (NRMSE) of each regression model. RESULTS: For all the data sets combined and for the WorldSID far-side data, CIBIC had the best goodness of fit, with R2 of 0.76 and 0.85. For frontal impacts with THOR and the combined ATD data set, DAMAGE had highest R2, 0.83 and 0.78, respectively. Injury criteria including translational accelerations were ranked lower, and BrIC were among the three lowest ranked for most data sets evaluated. UBrIC generally ranked after DAMAGE and CIBIC with respect to the goodness of fit but had the lowest NRMSE for all data sets. CONCLUSIONS: The two mass-spring-damper brain surrogate model criteria, DAMAGE and CIBIC, were best in capturing the head model MPS response for both the THOR and WorldSID data sets. BrIC had lower correlation to the head model MPS and performed marginally better than the linear acceleration only criteria for all the data sets combined. This study supports the suitability of DAMAGE and CIBIC as brain injury criteria to be used with THOR-50M and WorldSID-50M in vehicle crash test conditions, as they outperform BrIC.

Predicting occupant head displacements in evasive maneuvers; tuning and comparison of a rotational based and a translational based neck muscle controller.

Objective: Real-life car crashes are often preceded by an evasive maneuver, which can alter the occupant posture and muscle state. To simulate the occupant response in such maneuvers, human body models (HBMs) with active muscles have been developed. The aim of this study was to implement an omni-directional rotational head-neck muscle controller in the SAFER HBM and compare the bio-fidelity of the HBM with a rotational controller to the HBM with a translational controller, in simulations of evasive maneuvers. Methods: The rotational controller was developed using an axis-angle representation of head rotations, with x, y, and z components in the axis. Muscle load sharing was based on rotational direction in the simulation and muscle activity recorded in three volunteer experiments in these directions. The gains of the rotational and translational controller were tuned to minimize differences between translational and rotational head displacements of the HBM and volunteers in braking and lane change maneuvers using multi-objective optimizations. Bio-fidelity of the model with tuned controllers was evaluated objectively using CORrelation and Analysis (CORA). Results: The results indicated comparable performance for both controllers after tuning, with somewhat higher bio-fidelity for rotational kinematics with the translational controller. After tuning, good or excellent bio-fidelity was indicated for both controllers in the loading direction (forward in braking, and lateral in lane change), with CORA scores of 0.86-0.99 and 0.93-0.98 for the rotational and translational controllers, respectively. For rotational displacements, and translational displacements in the other directions, bio-fidelity ranged from poor to excellent, with slightly higher average CORA scores for the HBM with the translational controller in both braking and lane changing. Time-averaged muscle activity was within one standard deviation of time-averaged muscle activity from volunteers. Conclusion: Overall, the results show that when tuned, both the translational and rotational controllers can be used to predict the occupant response to an evasive maneuver, allowing for the inclusion of evasive maneuvers prior to a crash in evaluation of vehicle safety. The rotational controller shows potential in controlling omni-directional head displacements, but the translational controller outperformed the rotational controller. Thus, for now, the recommendation is to use the translational controller with tuned gains.

The influence of car passengers' sitting postures in intersection crashes.

Car passengers are frequently sitting in non-nominal postures and are able to perform a wide range of activities since they are not limited by tasks related to vehicle control, contrary to drivers. The anticipated introduction of Autonomous Driven vehicles could allow "drivers" to adopt similar postures and being involved in the same activities as passengers, allowing them a similar set of non-nominal postures. Therefore, the need to investigate the effects of non-nominal occupant sitting postures during relevant car crash events is becoming increasingly important. This study aims to investigate the effect of different postures of passengers in the front seat of a car on kinematic and kinetic responses during intersection crashes. A Human Body Model (HBM) was positioned in a numerical model of the front passenger seat of a midsize Sports Utility Vehicle (SUV) in a total of 35 postures, including variations to the lower and upper extremities, torso, and head postures. Three crash configurations, representative of predicted urban intersection crashes, were assessed in a simulation study; two side impacts, a near-side and a far-side, respectively, and a frontal impact. The occupant kinematics and internal loads were analyzed, and any deviation between the nominal and altered posture responses were quantified using cross-correlation of signals to highlight the most notable variations. Posture changes to the lower extremities had the largest overall influence on the lower extremities, pelvis, and whole-body responses for all crash configurations. In the frontal impact, crossing the legs allowed for the highest pelvis excursions and rotations, which affected the whole-body response the most. In the two side-impacts, leaning the torso in the coronal plane affected the torso and head kinematics by changing the interaction with the vehicle's interior. Additionally, in far-side impacts supporting the upper extremity on the center console resulted in increased torso excursions. Moreover, the response of the upper extremities was consistently sensitive to posture variations of all body regions.

A method for predicting crash configurations using counterfactual simulations and real-world data.

Traffic safety technologies revolve around two principle ideas; crash avoidance and injury mitigation for inevitable crashes. The development of relevant vehicle injury mitigating technologies should consider the interaction of those two technologies, ensuring that the inevitable crashes can be adequately managed by the occupant and vulnerable road user (VRU) protection systems. A step towards that is the accurate description of the expected crashes remaining when crash-avoiding technologies are available in vehicles. With the overall objective of facilitating the assessment of future traffic safety, this study develops a method for predicting crash configurations when introducing crash-avoiding countermeasures. The predicted crash configurations are one important factor for prioritizing the evaluation and development of future occupant and VRU protection systems. By using real-world traffic accident data to form the baseline and performing counterfactual model-in-the-loop (MIL) pre-crash simulations, the change in traffic situations (vehicle crashes) provided by vehicles with crash-avoiding technologies can be predicted. The method is built on a novel crash configuration definition, which supports further analysis of the in-crash phase. By clustering and grouping the remaining crashes, a limited number of crash configurations can be identified, still representing and covering the real-world variation. The developed method was applied using Swedish national- and in-depth accident data related to urban intersections and highway driving, and a conceptual Autonomous Emergency Braking system (AEB) computational model. Based on national crash data analysis, the conflict situations Same-Direction rear-end frontal (SD-ref) representing 53 % of highway vehicle-to-vehicle (v2v) crashes, and Straight Crossing Path (SCP) with 21 % of urban v2v intersection crashes were selected for this study. Pre-crash baselines, for SD-ref (n = 1010) and SCP (n = 4814), were prepared based on in-depth accident data and variations of these. Pre-crash simulations identified the crashes not avoided by the conceptual AEB, and the clustering of these revealed 5 and 52 representative crash configurations for the highway SD-ref and urban intersection SCP conflict situations, respectively, to be used in future crashworthiness studies. The results demonstrated a feasible way of identifying, in a predictive way, relevant crash configurations for in-crash testing of injury prevention capabilities.

Booster cushion design effects on child occupant kinematics and loading assessed using the PIPER 6-year-old HBM and the Q10 ATD in frontal impacts.

OBJECTIVE: Our objective was to study the effect on child occupant kinematics and loading by differences in booster cushion designs and attachment in a frontal impact. METHODS: Three different booster cushion designs were exposed to a frontal impact in vehicle rear seat interiors. The boosters were selected based on their difference in shape, stiffness, and guiding loop design. Tests were run varying the shoulder belt routing above or under the guiding loop, in addition to with or without attachment of the booster cushion to the vehicle ISOFIX anchorages. Eighteen simulations with the finite element PIPER 6-year-old human body model (HBM) were run investigating all combinations of parameters, in addition to 3 sled tests with a Q10 anthropomorphic test dummy (ATD). RESULTS: Across 2 different child sizes, using an HBM and an ATD, respectively, consistent sensitivity to the booster design differences were seen. Boosters providing similar initial static belt fit can result in different occupant responses during a crash, due to the design of the boosters and their dynamic performance. Compression of the booster cushion resulted in a delayed pelvis restraint, influencing the upper body kinematics. The guiding loop design as well as the belt routing above or under the guide also influenced the upper body kinematics and shoulder belt interaction. CONCLUSIONS: Early pelvis coupling to initiate torso pitch, and thereby an upper torso motion controlled by the shoulder belt, is the preferred occupant protection for booster-seated children. A stable mid-shoulder belt position centered over the chest initially is a prerequisite. Additionally, it was seen that the design of the guiding loops helps provide favorable interaction with the torso during the crash. The option to allow the shoulder belt to be placed above and under the guiding loops will accommodate a larger span of child sizes and adapt to more vehicle seat belt geometries. This study provides evidence that the design of the booster cushion plays an important role in creating an early pelvis coupling, as well as supporting favorable torso-shoulder belt interaction.

A female head-neck model for rear impact simulations.

Several mathematical cervical models of the 50th percentile male have been developed and used for impact biomechanics research. However, for the 50th percentile female no similar modelling efforts have been made, despite females being subject to a higher risk of soft tissue neck injuries. This is a limitation for the development of automotive protective systems addressing Whiplash Associated Disorders (WADs), most commonly caused in rear impacts, as the risk for females sustaining WAD symptoms is double that of males. In this study, a finite element head and neck model of a 50th percentile female was validated in rear impacts. A previously validated ligamentous cervical spine model was complemented with a rigid body head, soft tissues and muscles. In both physiological flexion-extension motions and simulated rear impacts, the kinematic response at segment level was comparable to that of human subjects. Evaluation of ligament stress levels in simulations with varied initial cervical curvature revealed that if an individual assumes a more lordotic posture than the neutral, a higher risk of WAD might occur in rear impact. The female head and neck model, together with a kinematical whole body model which is under development, addresses a need for tools for assessment of automotive protection systems for the group which is at the highest risk to sustain WAD.

Effects of whole spine alignment patterns on neck responses in rear end impact.

OBJECTIVE: The aim of this study was to investigate the whole spine alignment in automotive seated postures for both genders and the effects of the spinal alignment patterns on cervical vertebral motion in rear impact using a human finite element (FE) model. METHODS: Image data for 8 female and 7 male subjects in a seated posture acquired by an upright open magnetic resonance imaging (MRI) system were utilized. Spinal alignment was determined from the centers of the vertebrae and average spinal alignment patterns for both genders were estimated by multidimensional scaling (MDS). An occupant FE model of female average size (162 cm, 62 kg; the AF 50 size model) was developed by scaling THUMS AF 05. The average spinal alignment pattern for females was implemented in the model, and model validation was made with respect to female volunteer sled test data from rear end impacts. Thereafter, the average spinal alignment pattern for males and representative spinal alignments for all subjects were implemented in the validated female model, and additional FE simulations of the sled test were conducted to investigate effects of spinal alignment patterns on cervical vertebral motion. RESULTS: The estimated average spinal alignment pattern was slight kyphotic, or almost straight cervical and less-kyphotic thoracic spine for the females and lordotic cervical and more pronounced kyphotic thoracic spine for the males. The AF 50 size model with the female average spinal alignment exhibited spine straightening from upper thoracic vertebra level and showed larger intervertebral angular displacements in the cervical spine than the one with the male average spinal alignment. CONCLUSIONS: The cervical spine alignment is continuous with the thoracic spine, and a trend of the relationship between cervical spine and thoracic spinal alignment was shown in this study. Simulation results suggested that variations in thoracic spinal alignment had a potential impact on cervical spine motion as well as cervical spinal alignment in rear end impact condition.

A Female Ligamentous Cervical Spine Finite Element Model Validated for Physiological Loads.

Mathematical cervical spine models allow for studying of impact loading that can cause whiplash associated disorders (WAD). However, existing models only cover the male anthropometry, despite the female population being at a higher risk of sustaining WAD in automotive rear-end impacts. The aim of this study is to develop and validate a ligamentous cervical spine intended for biomechanical research on the effect of automotive impacts. A female model has the potential to aid the design of better protection systems as well as improve understanding of injury mechanisms causing WAD. A finite element (FE) mesh was created from surface data of the cervical vertebrae of a 26-year old female (stature 167 cm, weight 59 kg). Soft tissues were generated from the skeletal geometry and anatomical literature descriptions. Ligaments were modeled with nonlinear elastic orthotropic membrane elements, intervertebral disks as composites of nonlinear elastic bulk elements, and orthotropic anulus fibrosus fiber layers, while cortical and trabecular bones were modeled as isotropic plastic-elastic. The model has geometrical features representative of the female cervical spine-the largest average difference compared with published anthropometric female data was the vertebral body depth being 3.4% shorter for the model. The majority the cervical segments compare well with respect to biomechanical data at physiological loads, with the best match for flexion-extension loads and less biofidelity for axial rotation. An average female FE ligamentous cervical spine model was developed and validated with respect to physiological loading. In flexion-extension simulations with the developed female model and an existing average male cervical spine model, a greater range of motion (ROM) was found in the female model.

A human body model with active muscles for simulation of pretensioned restraints in autonomous braking interventions.

OBJECTIVE: The aim of this work is to study driver and passenger kinematics in autonomous braking scenarios, with and without pretensioned seat belts, using a whole-body finite element (FE) human body model (HBM) with active muscles. METHODS: Upper extremity musculature for elbow and shoulder flexion-extension feedback control was added to an HBM that was previously complemented with feedback controlled muscles for the trunk and neck. Controller gains were found using a radial basis function metamodel sampled by making 144 simulations of an 8 ms(-2) volunteer sled test. The HBM kinematics, interaction forces, and muscle activations were validated using a second volunteer data set for the passenger and driver positions, with and without 170 N seat belt pretension, in 11 ms(-2) autonomous braking deceleration. The HBM was then used for a parameter study in which seat belt pretension force and timing were varied from 170 to 570 N and from 0.25 s before to 0.15 s after deceleration onset, in an 11 ms(-2) autonomous braking scenario. RESULTS: The model validation showed that the forward displacements and interaction forces of the HBM correlated with those of corresponding volunteer tests. Muscle activations and head rotation angles were overestimated in the HBM when compared with volunteer data. With a standard seat belt in 11 ms(-2) autonomous braking interventions, the HBM exhibited peak forward head displacements of 153 and 232 mm for the driver and passenger positions. When 570 N seat belt pretension was applied 0.15 s before deceleration onset, a reduction of peak head displacements to 60 and 75 mm was predicted. CONCLUSIONS: Driver and passenger responses to autonomous braking with standard and pretensioned restraints were successfully modeled in a whole-body FE HBM with feedback controlled active muscles. Variations of belt pretension force level and timing revealed that belt pretension 0.15 s before deceleration onset had the largest effect in reducing forward head and torso movement caused by the autonomous brake intervention. The displacement of the head relative to the torso for the HBM is quite constant for all variations in timing and belt force; it is the reduced torso displacements that lead to reduced forward head displacements.

A method to model anticipatory postural control in driver braking events.

Human body models (HBMs) for vehicle occupant simulations have recently been extended with active muscles and postural control strategies. Feedback control has been used to model occupant responses to autonomous braking interventions. However, driver postural responses during driver initiated braking differ greatly from autonomous braking. In the present study, an anticipatory postural response was hypothesized, modelled in a whole-body HBM with feedback controlled muscles, and validated using existing volunteer data. The anticipatory response was modelled as a time dependent change in the reference value for the feedback controllers, which generates correcting moments to counteract the braking deceleration. The results showed that, in 11 m/s(2) driver braking simulations, including the anticipatory postural response reduced the peak forward displacement of the head by 100mm, of the shoulder by 30 mm, while the peak head flexion rotation was reduced by 18°. The HBM kinematic response was within a one standard deviation corridor of corresponding test data from volunteers performing maximum braking. It was concluded that the hypothesized anticipatory responses can be modelled by changing the reference positions of the individual joint feedback controllers that regulate muscle activation levels. The addition of anticipatory postural control muscle activations appears to explain the difference in occupant kinematics between driver and autonomous braking. This method of modelling postural reactions can be applied to the simulation of other driver voluntary actions, such as emergency avoidance by steering.

Simulation of active skeletal muscle tissue with a transversely isotropic viscohyperelastic continuum material model.

Human body models with biofidelic kinematics in vehicle pre-crash and crash simulations require a constitutive model of muscle tissue with both passive and active properties. Therefore, a transversely isotropic viscohyperelastic continuum material model with element-local fiber definition and activation capability is suggested for use with explicit finite element codes. Simulations of experiments with New Zealand rabbit's tibialis anterior muscle at three different strain rates were performed. Three different active force-length relations were used, where a robust performance of the material model was observed. The results were compared with the experimental data and the simulation results from a previous study, where the muscle tissue was modeled with a combination of discrete and continuum elements. The proposed material model compared favorably, and integrating the active properties of the muscle into a continuum material model opens for applications with complex muscle geometries.

Driver kinematic and muscle responses in braking events with standard and reversible pre-tensioned restraints: validation data for human models.

The objectives of this study are to generate validation data for human models intended for simulation of occupant kinematics in a pre-crash phase, and to evaluate the effect of an integrated safety system on driver kinematics and muscle responses. Eleven male and nine female volunteers, driving a passenger car on ordinary roads, performed maximum voluntary braking; they were also subjected to autonomous braking events with both standard and reversible pre-tensioned restraints. Kinematic data was acquired through film analysis, and surface electromyography (EMG) was recorded bilaterally for muscles in the neck, the upper extremities, and lumbar region. Maximum voluntary contractions (MVCs) were carried out in a driving posture for normalization of the EMG. Seat belt positions, interaction forces, and seat indentions were measured. During normal driving, all muscle activity was below 5% of MVC for females and 9% for males. The range of activity during steady state braking for males and females was 13-44% in the cervical and lumbar extensors, while antagonistic muscles showed a co-contraction of 2.3-19%. Seat belt pre-tension affects both the kinematic and muscle responses of drivers. In autonomous braking with standard restraints, muscle activation occurred in response to the inertial load. With pre-tensioned seat belts, EMG onset occurred earlier; between 71 ms and 176 ms after belt pre-tension. The EMG onset times decreased with repeated trials and were shorter for females than for males. With the results from this study, further improvement and validation of human models that incorporate active musculature will be made possible.

The occupant response to autonomous braking: a modeling approach that accounts for active musculature.

OBJECTIVE: The aim of this study is to model occupant kinematics in an autonomous braking event by using a finite element (FE) human body model (HBM) with active muscles as a step toward HBMs that can be used for injury prediction in integrated precrash and crash simulations. METHODS: Trunk and neck musculature was added to an existing FE HBM. Active muscle responses were achieved using a simplified implementation of 3 feedback controllers for head angle, neck angle, and angle of the lumbar spine. The HBM was compared with volunteer responses in sled tests with 10 ms(-2) deceleration over 0.2 s and in 1.4-s autonomous braking interventions with a peak deceleration of 6.7 ms(-2). RESULTS: The HBM captures the characteristics of the kinematics of volunteers in sled tests. Peak forward displacements have the same timing as for the volunteers, and lumbar muscle activation timing matches data from one of the volunteers. The responses of volunteers in autonomous braking interventions are mainly small head rotations and translational motions. This is captured by the HBM controller objective, which is to maintain the initial angular positions. The HBM response with active muscles is within ±1 standard deviation of the average volunteer response with respect to head displacements and angular rotation. CONCLUSIONS: With the implementation of feedback control of active musculature in an FE HBM it is possible to model the occupant response to autonomous braking interventions. The lumbar controller is important for the simulations of lap belt-restrained occupants; it is less important for the kinematics of occupants with a modern 3-point seat belt. Increasing head and neck controller gains provides a better correlation for head rotation, whereas it reduces the vertical head displacement and introduces oscillations.

Active muscle response using feedback control of a finite element human arm model.

Mathematical human body models (HBMs) are important research tools that are used to study the human response in car crash situations. Development of automotive safety systems requires the implementation of active muscle response in HBM, as novel safety systems also interact with vehicle occupants in the pre-crash phase. In this study, active muscle response was implemented using feedback control of a nonlinear muscle model in the right upper extremity of a finite element (FE) HBM. Hill-type line muscle elements were added, and the active and passive properties were assessed. Volunteer tests with low impact loading resulting in elbow flexion motions were performed. Simulations of posture maintenance in a gravity field and the volunteer tests were successfully conducted. It was concluded that feedback control of a nonlinear musculoskeletal model can be used to obtain posture maintenance and human-like reflexive responses in an FE HBM.