E-scooters as a mode of transportation is rapidly growing in popularity. This study evaluates head impact conditions and injury risk associated with E-scooter crashes. A multibody model of E-scooter falls induced by wheel-curb collision was built and compared with an experimental E-scooter crash test. A total of 162 crash scenarios were simulated to assess the effect of fall conditions (E-scooter initial speed and inclination, obstacle orientation, and user size) on the head impact kinematics. The forehead hit the ground first in 44% of simulations. The average tangential and normal impact speeds were 3.5 m/s and 4.8 m/s respectively. Nearly 100% of simulations identified a risk of concussion (linear acceleration peak >82 g and rotational acceleration peak >6383 rad/s²) and 90% of simulations suggested a risk of severe head injuries (HIC>700). This work provides preliminary data useful for the assessment and design of protective gears.

Understanding spinal cord injury requires a comprehensive knowledge of its mechanical properties, which remains debated due to the variability reported. This study aims to characterize the regional mechanical properties of the spinal cord in transverse sections using micro-indentation. Quasi-static indentations were performed on the entire surface of transverse slices obtained from 10 freshly harvested porcine thoracic spinal cords using a 0.5 mm diameter flat punch. No significant difference in average longitudinal elastic modulus was found between white matter (n = 183, E = 0.51 ± 0.21 kPa) and gray matter (n = 51, E = 0.53 ± 0.25 kPa). In the gray matter, the elastic modulus in the dorsal horn (0.48 ± 0.18 kPa) was significantly smaller than in the ventral horn (0.57 ± 0.24 kPa) (GLMM, p < 0.05). The elastic modulus in the dorsal horn was also significantly smaller than in the lateral (0.52 ± 0.22 kPa) and ventral funiculi (0.53 ± 0.18 kPa) of the white matter (GLMM, p < 0.05). However, there was no significant difference in the elastic modulus among the ventral, lateral and dorsal funiculi of the white matter (GLMM, p > 0.05). The average elastic modulus strongly varies between samples, ranging from 0.23 (±0.06) kPa to 0.79 (±0.18) kPa and the testing time postmortem was significantly associated with a decrease in elastic modulus (t = -5.2, p < 0.001). The spinal cord's white matter demonstrated significantly lower elastic modulus compared to published data on brain tissue tested under similar conditions. These findings enhance our comprehension of the mechanical properties of spinal cord white and gray matter, challenging the homogeneity assumption of current models.

The rapid increase in E-scooter usage has led to more scooter-related head and neck injuries. Yet, experimental data on head impacts and helmet effectiveness during crashes are scarce. The objectives of this study are to experimentally evaluate bicycle helmets in E-scooter falls, assessing head kinematics, impact conditions, and injury risks in two crash scenarios with and without helmets. Six E-scooter forward falls, induced by a curb collision at 20 km/h, were simulated in sled tests using a Hybrid III 50th anthropomorphic test device with and without a helmet. The curb was positioned either perpendicularly or at a 55° angle to the E-scooter's trajectory. Head velocity, head acceleration, neck load, chest acceleration, and chest deflection were measured. The average normal and tangential head velocities at impact were 5.9 m/s and 3.7 m/s, respectively. In configurations without helmet, both head accelerations and neck loads exceeded some injury thresholds, indicating a risk of severe injury. Using a helmet significantly reduced peak head linear (143 g vs. 571 g) and rotational (9.8 krad/s² vs. 23.1 krad/s²) accelerations, and Head Injury Criterion (HIC) (792 vs. 5868). However, it did not significantly affect peak head rotational velocity (44.5 rad/s vs. 41.5 rad/s), neck load (in flexion-compression) nor Neck Injury Criterion (NIJ) (1.2 vs. 1.0). The bicycle helmet significantly reduced most head injury metrics. Yet, the risk of severe head and neck injuries remains high. These results offer valuable data for evaluating head protection and developing and validating numerical crash test reconstructions for further investigations.

Identification of Traumatic axonal injury (TAI) is critical in clinical practice, particularly in terms of long-term prognosis, but also for medico-legal issues, to verify whether the death or the after-effects were attributable to trauma. Multidisciplinary approaches are an undeniable asset when it comes to solving these problems. The aim of this work is therefore to list the different techniques needed to identify axonal lesions and to understand the lesion mechanisms involved in their formation. Imaging can be used to assess the consequences of trauma, to identify indirect signs of TAI, to explain the patient's initial symptoms and even to assess the patient's prognosis. Three-dimensional reconstructions of the skull can highlight fractures suggestive of trauma. Microscopic and immunohistochemical techniques are currently considered as the most reliable tools for the early identification of TAI following trauma. Finite element models use mechanical equations to predict biomechanical parameters, such as tissue stresses and strains in the brain, when subjected to external forces, such as violent impacts to the head. These parameters, which are difficult to measure experimentally, are then used to predict the risk of injury. The integration of imaging data with finite element models allows researchers to create realistic and personalized computational models by incorporating actual geometry and properties obtained from imaging techniques. The personalization of these models makes their forensic approach particularly interesting.

Purpose: Each summer, many vacationers enjoy the Mediterranean Sea shores. Among the recreational nautical activities, motorboat cruise is a popular choice that leads to a significant number of thoracolumbar spine fractures at our clinic. This phenomenon seems to be underreported, and its injury mechanism remains unclear. Here, we aim to describe the fracture pattern and propose a possible mechanism of injury. Methods: We retrospectively reviewed the clinical, radiological, and contextual parameters of all motorboat-related spinal fracture cases during a 14-year period (2006–2020) in three French neurosurgical level I centers bordering the Mediterranean Sea. Fractures were classified according to the AOSpine thoracolumbar classification system. Results: A total of 79 patients presented 90 fractures altogether. Women presented more commonly than men (61/18). Most of the lesions occurred at the thoracolumbar transition region between T10 and L2 (88.9% of the levels fractured). Compression A type fractures were seen in all cases (100%). Only one case of posterior spinal element injury was observed. The occurrence of neurological deficit was rare (7.6%). The most commonly encountered context was a patient sitting at the boat’s bow, without anticipating the trauma, when the ship’s bow suddenly elevated while crossing another wave, resulting in a “deck-slap” mechanism hitting and propelling the patient in the air. Conclusions: Thoracolumbar compression fractures are a frequent finding in nautical tourism. Passengers seated at the boat’s bow are the typical victims. Some specific biomechanical patterns are involved with the boat’s deck suddenly elevating across the waves. More data with biomechanical studies are necessary to understand the phenomenon. Prevention and safety recommendations should be given before motorboat use to fight against these avoidable fractures.

Current standards require ski helmets to meet acceleration criteria during impacts to a rigid surface, but do not require helmets to be evaluated for head impacts to snow, which is a common cause of traumatic brain injury in skiing and snowboarding. The objective of this study is to measure head linear acceleration during impacts to snow, with and without a ski helmet. A portable test bench was developed and used to perform drop test of an instrumented headform onto groomed ski slopes. Impacts were made on the top of the head with and without a helmet, at three speeds (5.3 m/s, 6.1 m/s, 7.5 m/s) and on three types of snow (soft, hard, very hard). Head linear acceleration, HIC, snow hardness, and penetration of the head into the snow were recorded. Statistical analysis was performed using factorial ANOVAs. 96 impacts were performed. The mean peak head linear acceleration was 51G (±6G), 106G (±29G), and 170G (±27G) on soft, hard, and very hard snow, respectively, at 6.1 m/s. Head acceleration and HIC exceeded published thresholds for concussion and skull fracture in 85 and 28 impacts respectively. Head linear acceleration significantly increased with impact speed (p < 0.001) and snow stiffness (p < 0.001), but helmet use did not significantly reduce acceleration. The helmeted headform penetrated less into the snow than the non-helmeted headform. Helmet use did not significantly reduce head linear acceleration for the snow conditions tested. The study suggests that head-snow impact characteristics should be considered in the design and evaluation of future helmets.