Active neck musculature plays an important role in the response of the head and neck during impact and can affect the risk of injury. Finite element Human Body Models (HBM) have been proposed with open and closed-loop controllers for activation of muscle forces; however, the controllers in many current models are often calibrated to specific experimental loading cases, without considering the intrinsic role of physiologic muscle reflex mechanisms under different loading conditions. The goal of this study was to develop a closed-loop controller for a contemporary male HBM to represent muscle activation mechanisms based on the vestibulocollic and cervicocollic reflexes. Dual PID controllers were implemented, with head rotation and muscle stretch used for input.Controller parameters were optimized using volunteer data and then independently assessed across twelve impact conditions. The kinematics from the closed-loop controller simulations showed good average correlations to the experimental data (0.699) for the impacts. Compared to a previous optimized open-loop activation strategy, the average difference was less than 9%. The incorporation of the reflex mechanisms using a closedloop controller can provide robust performance for a range of impact directions and severities, which is critical to improving HBM response under a larger spectrum of automotive impact simulations.

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Diabetes mellitus (DM) in children is on the rise worldwide and it’s well established the relationship between it and obesity. The understanding of this risk factor for DM is critical to preventing the disease. The objective is to analyze epidemiological trends of weight in children, adding data from 2019. Temporal cross-sectional analysis of the years 2001, 2011 and 2019 was randomly done with children aged 5 to 9 years and proportionally selected from public and private schools in Feira de Santana, Bahia, Brazil. Overweight and obesity were defined using body mass index (BMI) ≥ the 85th and the 95th percentiles for age and gender, respectively. A total of 1.994 children were studied, being 699 (15.6±2.5 BMI; 366 [52%] girls; 7.1±1.3y), 714 (16.6±3.0 BMI; 348 [48.9%] girls; 7.6±1.4y), 581 (17.0±3.7 BMI; 303 [53.2%] girls; 6.9±2.2y) in 2001, 2011 and 2019 respectively. The excessive weight prevalence increased significantly from 2001, 2011 to 2019 (overweight [9.2%, 15.5% and 16.9%] and obesity [4.4%, 7.2%; 11.7%]) and normal weight decreased (86.4%, 68.6%, 61.9%) with p value <0.005 for all analyzes. Classifying by type of school, private (group 1) and public (group 2), in both groups comparing 2001, 2011 and 2019, the rate of normal weight decreased (84.2%, 68.6%, 59.4% for group 1 and 88.0%, 81.7% and 67.6% for group 2), also with significance. The prevalence of overweight significantly increased between 2001 and 2011 for both private (9.9%, 19.9%) and public (8.7%, 13.3%) sectors, but maintained itself stable for both between 2011 and 2019 (group 1[19.9%, 18.6%], group 2 [13.3%, 12.8%]). As for obesity, it did significantly increase in both groups through the entire period, at a rate of 6.0%, 11.5% and 13.2% in group 1 and 3.4%, 5.0% and 8.4% in group 2, respectively for 2001, 2011 and 2019. This trend towards increased prevalence of obesity in children from both the private and public sectors confirms the urgency in taking preventive measures to control not only obesity but its comorbidities such as DM. Disclosure A. Oliveira: None. F. Freitas: None. M. Clementino: None. L.G. Melo: None. D.C. Silva: None. P. Garcia: None. M. Correia: None. M. Mendes: None. M. Santos: None. A.A. Oliveira: None. T. Dechichi: None. A. Oliveira: None. A. Oliveira: None.

Quantifying the response of infill used to construct contemporary artificial turf is critical to the development of computational models and providing insights to reduce sports injury associated with artificial turf. In the current study, confined compression and direct shear tests were performed on typical infill materials (sand, SBR and two mixtures (33%: 67%) by-weight). The experimental tests exhibited a progression from high strength and stiffness (sand) to low strength and stiffness (SBR) with the mixtures having intermediate values. Increasing particle size, particularly sand, tended to increase the resistance of the infill to deformation. The experimental results were implemented into a soil constitutive material model and the experimental tests were simulated using a smoothed particle hydrodynamics (SPH) method to verify the implementation in a commercial explicit finite element solver. The SPH method successfully captured the initial loading up to yield, material flow and post-yield behavior, enabling large-scale particle flow that will be necessary to simulate artificial turf. The simulation results predicted the test force-displacement response well for SBR and mixture infills. The proposed methodology demonstrated the ability to measure properties of contemporary artificial turf infills in both compression and shear for pure sand, pure SBR and mixtures of the two, and use these properties to accurately represent the infill in a computational environment. The resulting model can be extended to large-scale turf models, to investigate athlete performance and injury risk when interacting with artificial turf.

Computational human body models (HBMs) can identify potential injury pathways not easily accessible through experimental studies, such as whiplash induced injuries. However, previous computational studies investigating neck response to simulated impact conditions have neglected the effect of pre‐impact neck posture and muscle pre‐tension on the intervertebral kinematics and tissue‐level response. The purpose of the present study was addressing this knowledge gap using a detailed neck model subjected to simulated low‐acceleration rear impact conditions, towards improved intervertebral kinematics and soft tissue response for injury assessment. An improved muscle path implementation in the model enabled the modeling of muscle pre‐tension using experimental muscle pre‐stretch data determined from previous cadaver studies. Cadaveric neck impact tests and human volunteer tests with the corresponding cervical spine posture were simulated using a detailed neck model with the reported boundary conditions and no muscle activation. Computed intervertebral kinematics of the model with pre‐tension achieved, for the first time, the S‐shape behavior of the neck observed in low severity rear impacts of both cadaver and volunteer studies. The maximum first principal strain in the muscles for the model with pre‐tension was 27% higher than that without pre‐tension. Although, the pre‐impact neck posture was updated to match the average posture reported in the experimental tests, the change in posture was generally small with only small changes in vertebral kinematics and muscle strain. This study provides a method to incorporate muscle pre‐tension in HBM and quantifies the importance of pre‐tension in calculating tissue‐level distractions.