The Influence of the Body on the Response of the Helmeted Head during Impact

According to helmet standards, the absorption capacity of helmets is assessed through impact of a headform fitted with the helmet onto an anvil. It implies that the effect of the rest of the body on impact outputs has been assumed to be negligible. The purpose of this work was to investigate this effect. Full-body and detached-head impacts were simulated using the Finite Element (FE) method. A detailed FE model of a composite-shell helmet was developed and validated against experimental data. It was coupled with an FE model of the Hybrid III dummy. To validate the full-body impact model, a new test method was designed to drop test helmeted dummies. As a consequence of the presence of the body, the crushing distance of the helmet liner was drastically increased. This evidence indicated that the effect of the body should be included in impact absorption tests in order to provide conditions that are more realistic to real world accidents and more stringent. The solution to an analytical model proposed for helmeted headform impacts revealed that the influence of increasing the headform mass on impact outputs, particularly the liner crushing distance, is the same as the influence of the body. The added mass was calculated for various impact configurations by using a detailed FE model of the human body. Finally, an added mass of 20% together with a 9% reduction in the limit of head linear acceleration were proposed. Full-body and detached-head oblique impacts were also simulated. The results indicated that the body had a noticeable influence on head rotational acceleration. Modifying the inertia matrix of the head to include this effect in the detached-head drop tests was proposed. By using an FE model of the human head, intracranial injury predictors were also evaluated in oblique impacts considering the complete kinematics of the head

A New Assessment of Bicycle Helmets: The Brain Injury Mitigation Effects of New Technologies in Oblique Impacts

New helmet technologies have been developed to improve the mitigation of traumatic brain injury (TBI) in bicycle accidents. However, their effectiveness under oblique impacts, which produce more strains in the brain in comparison with vertical impacts adopted by helmet standards, is still unclear. Here we used a new method to assess the brain injury prevention effects of 27 bicycle helmets in oblique impacts, including helmets fitted with a friction-reducing layer (MIPS), a shearing pad (SPIN), a wavy cellular liner (WaveCel), an airbag helmet (H\uf6vding) and a number of conventional helmets. We tested whether helmets fitted with the new technologies can provide better brain protection than conventional helmets. Each helmeted headform was dropped onto a 45\ub0 inclined anvil at 6.3 m/s at three locations, with each impact location producing a dominant head rotation about one anatomical axes of the head. A detailed computational model of TBI was used to determine strain distribution across the brain and in key anatomical regions, the corpus callosum and sulci. Our results show that, in comparison with conventional helmets, the majority of helmets incorporating new technologies significantly reduced peak rotational acceleration and velocity and maximal strain in corpus callosum and sulci. Only one helmet with MIPS significantly increased strain in the corpus collosum. The helmets fitted with MIPS and WaveCel were more effective in reducing strain in impacts producing sagittal rotations and a helmet fitted with SPIN in coronal rotations. The airbag helmet was effective in reducing brain strain in all impacts, however, peak rotational velocity and brain strain heavily depended on the analysis time. These results suggest that incorporating different impact locations in future oblique impact test methods and designing helmet technologies for the mitigation of head rotation in different planes are key to reducing brain injuries in bicycle accidents

A finite element model of cerebral vascular injury for predicting microbleeds location

Finite Element (FE) models of brain mechanics have improved our understanding of the brain response to rapid mechanical loads that produce traumatic brain injuries. However, these models have rarely incorporated vasculature, which limits their ability to predict the response of vessels to head impacts. To address this shortcoming, here we used high-resolution MRI scans to map the venous system anatomy at a submillimetre resolution. We then used this map to develop an FE model of veins and incorporated it in an anatomically detailed FE model of the brain. The model prediction of brain displacement at different locations was compared to controlled experiments on post-mortem human subject heads, yielding over 3,100 displacement curve comparisons, which showed fair to excellent correlation between them. We then used the model to predict the distribution of axial strains and strain rates in the veins of a rugby player who had small blood deposits in his white matter, known as microbleeds, after sustaining a head collision. We hypothesised that the distribution of axial strain and strain rate in veins can predict the pattern of microbleeds. We reconstructed the head collision using video footage and multi-body dynamics modelling and used the predicted head accelerations to load the FE model of vascular injury. The model predicted large axial strains in veins where microbleeds were detected. A region of interest analysis using white matter tracts showed that the tract group with microbleeds had 95th percentile peak axial strain and strain rate of 0.197 and 64.9 s−1 respectively, which were significantly larger than those of the group of tracts without microbleeds (0.163 and 57.0 s−1). This study does not derive a threshold for the onset of microbleeds as it investigated a single case, but it provides evidence for a link between strain and strain rate applied to veins during head impacts and structural damage and allows for future work to generate threshold values. Moreover, our results suggest that the FE model has the potential to be used to predict intracranial vascular injuries after TBI, providing a more objective tool for TBI assessment and improving protection against it

Design Methodology for Magnetic Field-Based Soft Tri-Axis Tactile Sensors

Tactile sensors are essential if robots are to safely interact with the external world and to dexterously manipulate objects. Current tactile sensors have limitations restricting their use, notably being too fragile or having limited performance. Magnetic field-based soft tactile sensors offer a potential improvement, being durable, low cost, accurate and high bandwidth, but they are relatively undeveloped because of the complexities involved in design and calibration. This paper presents a general design methodology for magnetic field-based three-axis soft tactile sensors, enabling researchers to easily develop specific tactile sensors for a variety of applications. All aspects (design, fabrication, calibration and evaluation) of the development of tri-axis soft tactile sensors are presented and discussed. A moving least square approach is used to decouple and convert the magnetic field signal to force output to eliminate non-linearity and cross-talk effects. A case study of a tactile sensor prototype, MagOne, was developed. This achieved a resolution of 1.42 mN in normal force measurement (0.71 mN in shear force), good output repeatability and has a maximum hysteresis error of 3.4%. These results outperform comparable sensors reported previously, highlighting the efficacy of our methodology for sensor design

Design Optimisation of a Magnetic Field Based Soft Tactile Sensor

This paper investigates the design optimisation of a magnetic field based soft tactile sensor, comprised of a magnet and Hall effect module separated by an elastomer. The aim was to minimise sensitivity of the output force with respect to the input magnetic field; this was achieved by varying the geometry and material properties. Finite element simulations determined the magnetic field and structural behaviour under load. Genetic programming produced phenomenological expressions describing these responses. Optimisation studies constrained by a measurable force and stable loading conditions were conducted; these produced Pareto sets of designs from which the optimal sensor characteristics were selected. The optimisation demonstrated a compromise between sensitivity and the measurable force, a fabricated version of the optimised sensor validated the improvements made using this methodology. The approach presented can be applied in general for optimising soft tactile sensor designs over a range of applications and sensing modes

Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports

Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes

An instrumented mouthguard for real-time measurement of head kinematics under a large range of sport specific accelerations

Background: Head impacts in sports can produce brain injuries. The accurate quantification of head kinematics through instrumented mouthguards (iMG) can help identify underlying brain motion during injurious impacts. The aim of the current study is to assess the validity of an iMG across a large range of linear and rotational accelerations to allow for on-field head impact monitoring. Methods: Drop tests of an instrumented helmeted anthropometric testing device (ATD) were performed across a range of impact magnitudes and locations, with iMG measures collected concurrently. ATD and iMG kinematics were also fed forward to high-fidelity brain models to predict maximal principal strain. Results: The impacts produced a wide range of head kinematics (16–171 g, 1330–10,164 rad/s2 and 11.3–41.5 rad/s) and durations (6–18 ms), representing impacts in rugby and boxing. Comparison of the peak values across ATD and iMG indicated high levels of agreement, with a total concordance correlation coefficient of 0.97 for peak impact kinematics and 0.97 for predicted brain strain. We also found good agreement between iMG and ATD measured time-series kinematic data, with the highest normalized root mean squared error for rotational velocity (5.47 ± 2.61%) and the lowest for rotational acceleration (1.24 ± 0.86%). Our results confirm that the iMG can reliably measure laboratory-based head kinematics under a large range of accelerations and is suitable for future on-field validity assessments

The impact attenuation test of motorcycle helmet standards.

In this paper, the methods of the European (UNECE22.05), American (FMVSS218), British (BS6658), Australia and New Zealand (AS/NZS1698) and Snell (M2010) standards for evaluating the impact absorption performance of motorcycle helmets are described and compared. The compared features are the test apparatus, impact initial conditions, impact points, impact output and the approval limit. This comparison reveals that these standards adopt the same method for evaluating the impact performance of helmets, which is positioning the helmet on a metal headform and dropping them onto a rigid anvil. During impact, the linear acceleration of the centre of gravity of the headform is measured; the approval criterion is based on this acceleration. Several studies on the relevance of this test method to real-life accidents are reviewed and their main findings are summarised. The review includes studies on the interaction between the head and neck during helmeted head impacts and those on assessing the performance of helmets during oblique impacts by using rotational acceleration, along with linear acceleration. It appears that in both areas, more research needs to be carried out to be able to influence current standards

Evaluation of the effective mass of the body for helmet impacts

Currently available motorcycle helmet standards employ headforms to assess the impact absorption capability of helmets. The mass and size of the headforms are similar to those of the human head. This fact implies that the standards rely on the assumption that the effect of the rest of the body on the performance of the helmet during impact is negligible. In this study, by using validated finite element (FE) models of a commercially available helmet and of the human body, full-body helmet impacts are simulated. Even within the short duration of the impacts (less than 10 ms), the body interacts with the head, leading to further crushing of the helmet liner. To include this effect in the headform impacts, the mass of the headform is increased. The added mass is determined for various impact configurations. It is found that the added mass is not dependent on the properties of the helmet; thus, it can be adopted by the impact absorption test of standards