Injury Biomechanics Research Research Articles

Forward dynamics computational modelling of a cyclist fall with the inclusion of protective response using deep learning-based human pose estimation

Single bicycle crashes, i.e., falls and impacts not involving a collision with another road user, are a significantly underestimated road safety problem. The motions and behaviours of falling people, or fall kinematics, are often investigated in the injury biomechanics research field. Understanding the mechanics of a fall can help researchers develop better protective gear and safety measures to reduce the risk of injury. However, little is known about cyclist fall kinematics or dynamics.Therefore, in this study, a video analysis of cyclist falls is performed to investigate common kinematic forms and impact patterns. Furthermore, a pipeline involving deep learning-based human pose estimation and inverse kinematics optimisation is created for extracting human motion from real-world footage of falls to initialise forward dynamics computational human body models. A bracing active response is then optimised for using a genetic algorithm. This is then applied to a case study of a cyclist fall.The kinematic forms characterised in this study can be used to inform initial conditions for computational modelling and injury estimation in cyclist falls. Findings indicate that protective response is an important consideration in fall kinematics and dynamics, and should be included in computational modelling. Furthermore, the novel reconstruction pipeline proposed here can be applied more broadly for traumatic injury biomechanics tasks. The tool developed in this study is available at https://kevgildea.github.io/KinePose/.

Geometric and Inertial Properties of the Pig Head and Brain in an Anatomical Coordinate System.

Porcine models in injury biomechanics research often involve measuring head or brain kinematics. Translation of data from porcine models to other biomechanical models requires geometric and inertial properties of the pig head and brain, and a translationally relevant anatomical coordinate system (ACS). In this study, the head and brain mass, center of mass (CoM), and mass moments of inertia (MoI) were characterized, and an ACS was proposed for the pre-adolescent domestic pig. Density-calibrated computed tomography scans were obtained for the heads of eleven Large White × Landrace pigs (18-48kg) and were segmented. An ACS with a porcine-equivalent Frankfort plane was defined using externally palpable landmarks (right/left frontal process of the zygomatic bone and zygomatic process of the frontal bone). The head and brain constituted 7.80 ± 0.79% and 0.33 ± 0.08% of the body mass, respectively. The head and brain CoMs were primarily ventral and caudal to the ACS origin, respectively. The mean head and brain principal MoI (in the ACS with origin at respective CoM) ranged from 61.7 to 109.7kgcm2, and 0.2 to 0.6kgcm2, respectively. These data may aid the comparison of head and brain kinematics/kinetics data and the translation between porcine and human injury models.

Focusing on vulnerable populations in crashes: recent advances in finite element human models for injury biomechanics research

Focusing on vulnerable populations in crashes: recent advances in finite element human models for injury biomechanics research

An assessment of blast modelling techniques for injury biomechanics research.

Blast-induced traumatic brain injury (TBI) has been affecting combatants and civilians. The blast pressure wave is thought to have a significant contribution to blast-related TBI. Due to the limitations and difficulties of conducting blast tests on surrogates, computational modelling has been used as a key method for exploring this field. However, the blast wave modelling methods reported in current literature have drawbacks. They either cannot generate the desirable blast pressure wave history or they are unable to accurately simulate the blast wave/structure interaction. In addition, boundary conditions, which can have significant effects on model predictions, have not been described adequately. Here, we critically assess the commonly used methods for simulating blast wave propagation in air (open-field blast) and its interaction with the human body. We investigate the predicted blast wave time history, blast wave transmission, and the effects of various boundary conditions in three-dimensional (3D) models of blast prediction. We propose a suitable meshing topology, which enables accurate prediction of blast wave propagation and interaction with the human head and significantly decreases the computational cost in 3D simulations. Finally, we predict strain and strain rate in the human brain during blast wave exposure and show the influence of the blast wave modelling methods on the brain response. The findings presented here can serve as guidelines for accurately modelling blast wave generation and interaction with the human body for injury biomechanics studies and design of prevention systems.

The applied impact of ‘naïve’ statistical modelling of clustered observations of motion data in injury biomechanics research

ObjectivesAppropriate statistical analysis of clustered data necessitates accounting for within-participant effects to ensure results are repeatable and translatable to real-world applications. This study aimed to compare statistical output and injury risk interpretation differences from two statistical regression models built from a clinical movement sidestepping database. A “naïve” regression model, which does not account for within-participant effects, was compared with an appropriately applied mixed effects model. DesignComparative study. MethodsThree-dimensional unplanned sidestepping joint angle data (trunk, hip, and knee) from 35 males (112 observations) were used to model peak knee valgus moments and anterior cruciate ligament injury risk during the impact phase of stance. Both statistical models were cross-validated using a k-fold analysis. ResultsThe naïve regression returned inflated goodness of fit statistics (R2=0.50), which was evident following cross-validation (predicted R2=0.43). Following cross-validation, the mixed effects model (predicted R2=0.40) explained a similar amount of variance, despite containing three less predictors. The naïve model produced inaccurate parameter estimates, overestimating the effects of certain kinematic parameters by as much as 79 %. ConclusionsA regression model naïvely applied to clustered observations of sidestepping data resulted in erroneous parameter estimates and goodness of fit statistics which have the potential to mislead future research and real-world applications. It is important for sport and clinical scientists to use statistically appropriate mixed effects models when modelling clustered motion capture data for injury biomechanics research to protect the translatability of the findings.

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

ABSTRACTObjective: 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.

Comparison of two scaling approaches for the development of biomechanical multi-body human models

Dimensional scaling approaches are widely used to develop multi-body human models in injury biomechanics research. Given the limited experimental data for any particular anthropometry, a validated model can be scaled to different sizes to reflect the biological variance of population and used to characterize the human response. This paper compares two scaling approaches at the whole-body level: one is the conventional mass-based scaling approach which assumes geometric similarity; the other is the structure-based approach which assumes additional structural similarity by using idealized mechanical models to account for the specific anatomy and expected loading conditions. Given the use of exterior body dimensions and a uniform Young’s modulus, the two approaches showed close values of the scaling factors for most body regions, with 1.5 % difference on force scaling factors and 13.5 % difference on moment scaling factors, on average. One exception was on the thoracic modeling, with 19.3 % difference on the scaling factor of the deflection. Two 6-year-old child models were generated from a baseline adult model as application example and were evaluated using recent biomechanical data from cadaveric pediatric experiments. The scaled models predicted similar impact responses of the thorax and lower extremity, which were within the experimental corridors; and suggested further consideration of age-specific structural change of the pelvis. Towards improved scaling methods to develop biofidelic human models, this comparative analysis suggests further investigation on interior anatomical geometry and detailed biological material properties associated with the demographic range of the population.

The tolerance of the human body to automobile collision impact – a systematic review of injury biomechanics research, 1990–2009

Road traffic injuries account for 1.3 million deaths per year world-wide. Mitigating both fatalities and injuries requires a detailed understanding of the tolerance of the human body to external load. To identify research priorities, it is necessary to periodically compare trends in injury tolerance research to the characteristics of injuries occurring in the field. This study sought to perform a systematic review on the last twenty years of experimental injury tolerance research, and to evaluate those results relative to available epidemiologic data. Four hundred and eight experimental injury tolerance studies from 1990–2009 were identified from a reference index of over 68,000 papers. Examined variables included the body regions, ages, and genders studied; and the experimental models used. Most (20%) of the publications studied injury to the spine. There has also been a substantial volume of biomechanical research focused on upper and lower extremity injury, thoracic injury, and injury to the elderly – although these injury types still occur with regularity in the field. In contrast, information on pediatric injury and physiological injury (especially in the central nervous system) remains lacking. Given their frequency of injury in the field, future efforts should also include improving our understanding of tolerances and protection of vulnerable road users (e.g., motorcyclists, pedestrians).

Response

Dear Editor-in-Chief, Thank you for the opportunity to respond to the letter from Drs. Greenwald, Beckwith, Crisco, and Wilcox that raised concerns about the methodology and interpretation in our article (1). The authors highlight research in which the Head Impact Telemetry (HIT) System’s ability to detect impact has been corroborated through video review. These studies are designed to observe false positives—the HIT System reports a head impact that did not occur. However, these studies cannot identify false negatives—the HIT System does not report an impact that did occur. Like our study, which can and did detect false negatives, others (4) report a false-negative rate of approximately 20%. In the letter, the authors note that our article reported higher errors (lower coefficients of determination) than previously reported, but they incorrectly attribute this to limitations in our experimental protocol. The primary reason, however, is the difference in the error calculation method (see our Discussion, paragraph 3). We used a more conventional approach in statistical analyses (6) to estimate error associated with a given single measurement from the HIT System. Using this traditional definition of error with the data published in the most recent validation of the football HIT System in the letter of the authors (3), the error is 14% for linear acceleration, which is slightly lower than the error we reported (18%–31%) and greater than the 0.9% error reported in that article. In the letter, the authors raised concerns about the test biofidelity. The laboratory setting is generally a simplified analog of the real world, allowing for a systematic evaluation of test parameters on the outcomes of interest. We evaluated a range of impact directions and velocities, and we acknowledged (Discussion section, paragraphs 6–10) that other parameters such as fit, size, and material of the impacting surface likely influence the response. We elected to use the Hybrid III head form with limited structure on the underside of the chin and a spherical impacting ram for our testing to mimic published boxing (2) and football (3,5) studies by the authors. This, combined with the consistency of error results cited in the previous paragraph, suggests that our test protocol is as biofidelic as what has been used previously. Lastly, in the letter, the authors state that we “recommend applying [our] laboratory-derived ‘calibration factors’ to on-ice data without first considering plausibility.” We clearly stated in the Discussion (paragraph 4) that the published calibration factors “have potential,” but “further development of robust calibration equations should be subject of future study.” We commend the letter of the authors for developing the HIT technology and a business model that seeks to reduce the burden of TBI on society. We feel strongly, however, that the accuracy of such systems must be rigorously quantified as coaches and parents will make decisions about concussion risk and return to play based on player-specific data from such systems. We agree with the authors’ letter that validation is a multiphase process, and we recognize differences between in-play use and laboratory testing. Future research should incorporate laboratory-defined sensor accuracy into on-field investigations of injury risk and exposure. Kristy B. Arbogast, PhD Center for Injury Research and Prevention The Children’s Hospital of Philadelphia Department of Pediatrics, University of Pennsylvania Philadelphia, PA Mari A. Allison, BS Center for Injury Research and Prevention The Children’s Hospital of Philadelphia Department of Bioengineering University of Pennsylvania Philadelphia, PA Matthew R. Maltese, PhD Department of Anesthesiology and Critical Care Medicine, The Children’s Hospital of Philadelphia Philadelphia, PA John H. Bolte IV, PhD Yun Seok Kang, PhD Injury Biomechanics Research Laboratory The Ohio State University Columbus, OH

Multibody modelling of a TB31 and a TB32 crash test with vertical portable concrete barriers: Model verification and sensitivity analysis

In this article the multibody simulation software package MADYMO for analysing and optimizing occupant safety design was used to model crash tests for Normal Containment barriers in accordance with EN 1317. The verification process was carried out by simulating a TB31 and a TB32 crash test performed on vertical portable concrete barriers and by comparing the numerical results to those obtained experimentally. The same modelling approach was applied to both tests to evaluate the predictive capacity of the modelling at two different impact speeds. A sensitivity analysis of the vehicle stiffness was also carried out. The capacity to predict all of the principal EN1317 criteria was assessed for the first time: the acceleration severity index, the theoretical head impact velocity, the barrier working width and the vehicle exit box. Results showed a maximum error of 6% for the acceleration severity index and 21% for theoretical head impact velocity for the numerical simulation in comparison to the recorded data. The exit box position was predicted with a maximum error of 4°. For the working width, a large percentage difference was observed for test TB31 due to the small absolute value of the barrier deflection but the results were well within the limit value from the standard for both tests. The sensitivity analysis showed the robustness of the modelling with respect to contact stiffness increase of ±20% and ±40%. This is the first multibody model of portable concrete barriers that can reproduce not only the acceleration severity index but all the test criteria of EN 1317 and is therefore a valuable tool for new product development and for injury biomechanics research.

Human surrogates for injury biomechanics research

This article reviews the attributes of the human surrogates most commonly used in injury biomechanics research. In particular, the merits of human cadavers, human volunteers, animals, dummies, and computational models are assessed relative to their ability to characterize the living human response and injury in an impact environment. Although data obtained from these surrogates have enabled biomechanical engineers and designers to develop effective injury countermeasures for occupants and pedestrians involved in crashes, the magnitude of the traffic safety problem necessitates expanded efforts in research and development. This article makes the case that while there are limitations and challenges associated with any particular surrogate, each provides a critical and necessary component in the continued quest to reduce crash-related injuries and fatalities.

Injury Biomechanics and Child Abuse

Child abuse is a leading cause of morbidity and mortality in young children and infants in the United States. Medical care providers, social services, and legal systems make critical decisions regarding injury and history plausibility daily. Injury plausibility judgments rely on evidence-based medicine, individualized experiences, and empirical data. A poor outcome may result if abuse is missed or an innocent family is accused, therefore evidence and science-based injury assessments are required. Although research in biomechanics has improved clinical understanding of injuries in children, much work is still required to develop a more scientific, rigorous approach to assessing injury causation. This article reviews key issues in child abuse and how injury biomechanics research may help improve accuracy in differentiating abuse from accidental events. Case-based biomechanical investigations, human surrogate, and computer modeling biomechanics research applied to child abuse injury are discussed. The goal of this paper is to provide an overview of key research studies rather than on review or commentary articles. Limitations and future research needs are also reviewed.

A limited review of finite element models developed for brain injury biomechanics research

In this paper, finite element models developed at Wayne State University to study impact injury biomechanics of the human brain were reviewed. The complexity of these models has been augmented significantly over the years in order to allow each new version of the model to address additional clinical phenomena or to make site-specific correlation between the computer model and biological data. Even though all available data have been used for validation of the latest model, it can only be considered partially validated because there is a lack of quantitative data for a complete validation. Nevertheless, useful information has been derived from model predictions. New and higher quality experimental or real world data are needed for making continued improvement to computer models so that they can accurately predict the risk of brain injury in a given impact.

Force transmission and stress distribution in a computer-simulated model of the kidney: an analysis of the injury mechanisms in renal trauma.

Injury mechanisms in renal trauma were investigated by analyzing the stress distributions within a two-dimensional computer-simulated model of the kidney. In biomechanics, damage to biological tissue is primarily caused by stresses resulting in tissue deformation beyond recovery limits. Segmental surface force was applied to the model and the resulting stress distributions were analyzed. Maximum stress concentrations were found at the periphery of the kidney model. Stresses were caused by the combined effect of the applied force and the reaction generated by the liquid-filled inner compartment as a function of its hydrostatic pressure. Maximum stress concentrations corresponded to typical injury sites observed clinically. Our findings suggest that a similar mechanism may play a crucial role in renal trauma. Renal injuries as well as the higher trauma susceptibility of hydronephrotic kidneys and renal cysts could thus be explained. The role of computer models in injury biomechanics research is discussed.

Humanitarian benefits of cadaver research on injury prevention.

This paper discusses the value of human cadaveric subjects in injury biomechanics research. Published data were used to estimate the number of cadavers used in the past 30 years and to show that, as a benefit to society, over 60 lives were saved and countless injuries prevented for each cadaver used in the development and validation of safety improvements. Ethical and religious concerns regarding the use of cadavers are also addressed. Because of the substantial humanitarian value of cadaver research and the lack of suitable specimens, it is proposed that cadaver resources be pooled and that institutions with surplus specimens supply the few cadaver testing laboratories with specimens each year. This approach will enable further development of safety systems and facilitate achieving the national goals for injury control.

Literature review of head injury biomechanics

The high incidence of head injuries resulting from transportation system crashes, sports, military activities, falls, assaults, etc. contributes to a preponderance of head injury biomechanics research. A wealth of publications result, addressing phenomenological and mechanistic issues associated with head response to mechanical impact. This literature survey provides an assessment of hypothesized brain injury mechanisms, brain injury criteria, mathematical models of head injury and available techniques for measuring head kinematics and brain tissue deformations associated with exposure to dynamic loads.

Injury biomechanics research: An essential element in the prevention of trauma

The central aspects of injury biomechanics research are defined and research approaches described. These aspects include the identification and definition of impact injury mechanisms, the quantification of biomechanical response to impact, the determination of impact tolerance levels, and the development and use of injury assessment devices and techniques for evaluating injury prevention systems. The current status of knowledge and technology is then reviewed for the head, cervical spine, thorax, abdomen, and lower extremity. Important gaps are identified, and research priorities emphasizing functional impairment are proposed.