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BACKGROUND/OBJECTIVE: Headgear designed to protect girls lacrosse athletes is widely available and permitted for voluntary use; however, it remains unknown how policies mandating headgear use may change the sport and, particularly regarding impacts during game-play. Therefore, this study compares the impact rates and game play characteristics of girls high school lacrosse in Florida which mandates headgear use (HM), with states having no headgear mandate (NHM). MATERIALS AND METHODS: Video from 189 randomly-selected games (HM: 64, NHM: 125) were analyzed. Descriptive statistics, Impact Rates (IR), Impact Rate Ratios (IRR), Impact Proportion Ratios (IPR), and 95% Confidence Intervals (CI) were calculated. IRRs and IPRs with corresponding CIs that excluded 1.00 were deemed statistically significant. RESULTS: 16,340 impacts (HM:5,821 NHM: 10,519; 86.6 impacts/game, CI: 88.6-93.3) were identified using the Lacrosse Incident Analysis Instrument (LIAI). Most impacts directly struck the body (n = 16,010, 98%). A minority of impacts directly struck a players head (n = 330, 2%). The rate of head impacts was significantly higher in the HM cohort than NHM cohort (IRR = 2.1; 95% CI = 1.7-2.6). Most head impacts (n = 271, 82%) were caused by stick contact in both groups. There was no difference in the proportion of penalties administered for head impacts caused by stick contact between the HM and NHM cohorts (IPR IRRHM/NHM = 0.98; CI = 0.79-1.16). However, there was a significantly greater proportion of head impacts caused by player contact that resulted in a penalty administered in the HM cohort (IPR = 1.44 CI = 1.17-1.54). CONCLUSION: These findings demonstrate that mandating headgear use was associated with a two-fold greater likelihood of sustaining a head impact during game play compared to NHM states. A majority of head impacts in both HM and NHM states were caused by illegal stick contact that did not result in penalty.

It is of profound significance to detect whether cyclists wear helmets to protect their personal safety and maintain road traffic safety. Due to the limitations of space, distance and cyclist movement, it is challenging to detect helmet-wearing accurately and quickly. In view of this, a novel You Only Look Once (YOLOv8) algorithm for helmet-wearing detection is suggested in this paper. Firstly, YOLOv8n with the best performance test results is selected as the baseline model from several advanced object detection algorithms. Secondly, improvement measures are taken for YOLOv8n. The squeeze-and-excitation networks (SENet) is integrated at the C2f of the neck to improve the network representation ability. Part of conv modules in the backbone is replaced with the lightweight convolution (LConv) to improve the computational efficiency and the generalization ability of the model. The loss function is changed with the Wise-IoU (WIoU), to enhance the overall performance of the model. Additionally, the reasoning method is replaced by the slicing aided hyper inference (SAHI), which aims to lower the rate of missed detections for smaller objects and strengthen the accuracy of their detection. Through the above improvement methods, a new helmet-wearing detection algorithm is formed, called helmet net. Furthermore, in comparison to the YOLOv8n, the proposed algorism demonstrated an increase in precision, recall, and mean average precision (mAP) by 5, 7.3, and 6.4%, respectively, for helmet-wearing detection. At the same time, the speed reaches 111.1 fps, which can contribute to the real-time detection of helmet-wearing. After adding SAHI, the detection results show that the model can detect more small objects, which further enhances the competence of model for helmet-wearing detection. [ABSTRACT FROM AUTHOR]

AbstractHigh-velocity bullet impact (velocity: 700 ± 15 m/s) is a significant concern during asymmetric warfare. Ballistic helmets for high-velocity bullet impact and associated biomechanical responses of the headforms are actively sought. Further, data on the performance of ballistic helmets against high-velocity impact are not available in the literature. Toward this end, we have evaluated the performance of Patka (helmet) against high-velocity bullet impact. Patka was mounted on various headforms to assess the perforation of the Patka by the bullet and to measure various biomechanical parameters such as back face deformation (BFD), head kinematics, brain simulant pressures, and neck loads. Bullet impact in front and oblique (30° right to the sagittal axis) orientations were considered. Our results suggest that the Patka was effective in mitigating the high-velocity bullet impact. Perforation of the Patka by the bullet was not observed. BFD in the witness material was negligible (<1 mm). Measured head kinematics and brain simulant pressures were comparable to the quantities typically reported during low- and medium-velocity bullet impacts. Further, most of the biomechanical responses, except angular acceleration and neck force, were below 50% injury risk for mild traumatic brain injury (mTBI). Despite these encouraging trends, the shattering of bullets into fragments was also observed. These fragments traveled a considerable distance at reasonable velocities. This work provides unique insights regarding the performance of Patka and associated biomechanical responses of the headforms against high-velocity bullet impact, with implications in the design and evaluation of futuristic ballistic helmets.TERMINOLOGIESBallistic threat level: Ballistic threat levels are defined based on the impact velocity of the bullet. Different types of bullets are proposed to achieve the desired impact velocities corresponding to different ballistic threat levels.Ballistic helmet: Ballistic helmet is a type of protective headgear designed to protect the wearer head from potentially fatal impacts during combat operations.Ballistic performance: Ballistic performance of the helmet is evaluated based on the perforation resistance capacity of the helmet and back face deformation (BFD) of the helmet.Back face deformation (BFD): Back face deformation (BFD) of the helmet refers to the localized dent or bulge in the inner layer of the helmet due to ballistic impact. BFD is measured as a depth of indent in the witness material (e.g., Roma Plastilina #1 clay) of the cruciform cavity-based headform.Headform: Headform is a model of the human head replicating a few of the anatomical and material aspects. Headforms can vary in design and complexity based on the intended applications.Patka: Patka is a protective headgear designed to provide ballistic protection to the head against high-velocity threat (impact velocity: 700 ± 15 m/s). Patka is made up of hardened (armour) steel material.Head kinematics: Head kinematics refers to the motion of the head typically measured in terms of linear acceleration and angular velocity.Neck loads: Neck loads refer to the forces and moments experienced by the neck during a static or dynamic event.Brain simulant pressure: Brain simulant pressure is a hydrodynamic pressure generated within the brain simulant.Ballistic threat level: Ballistic threat levels are defined based on the impact velocity of the bullet. Different types of bullets are proposed to achieve the desired impact velocities corresponding to different ballistic threat levels.Ballistic helmet: Ballistic helmet is a type of protective headgear designed to protect the wearer head from potentially fatal impacts during combat operations.Ballistic performance: Ballistic performance of the helmet is evaluated based on the perforation resistance capacity of the helmet and back face deformation (BFD) of the helmet.Back face deformation (BFD): Back face deformation (BFD) of the helmet refers to the localized dent or bulge in the inner layer of the helmet due to ballistic impact. BFD is measured as a depth of indent in the witness material (e.g., Roma Plastilina #1 clay) of the cruciform cavity-based headform.Headform: Headform is a model of the human head replicating a few of the anatomical and material aspects. Headforms can vary in design and complexity based on the intended applications.Patka: Patka is a protective headgear designed to provide ballistic protection to the head against high-velocity threat (impact velocity: 700 ± 15 m/s). Patka is made up of hardened (armour) steel material.Head kinematics: Head kinematics refers to the motion of the head typically measured in terms of linear acceleration and angular velocity.Neck loads: Neck loads refer to the forces and moments experienced by the neck during a static or dynamic event.Brain simulant pressure: Brain simulant pressure is a hydrodynamic pressure generated within the brain simulant. [ABSTRACT FROM AUTHOR]

Objective: To explore diverse stakeholders' perceptions of headgear use in collegiate women's lacrosse. Participants: 189 collegiate women's lacrosse stakeholders (players: n = 87; coaches: n = 71; officials: n = 32). Methods: Participants completed online open-ended qualitative questions surrounding headgear use in the sport. Responses were coded by the research team via inductive reasoning. Results: Stakeholders felt that incorporating headgear use into women's lacrosse would increase aggression and change the nature of the sport. Some felt that headgear was important for injury risk mitigation and invoked a need for research and development. Stakeholders raised the need for coaching and officiating improvement as primary injury prevention measures. Players were concerned about esthetics and performance limitations. Finally, many felt that it should be left to player choice to wear headgear or not. Conclusion: Most stakeholders invoke concerns of risk compensation and changing the nature of the sport of women's lacrosse, and are in favor of headgear remaining optional. [ABSTRACT FROM AUTHOR]

Blunt force trauma remains a serious threat to many populations and is commonly seen in motor vehicle crashes, sports, and military environments. Effective design of helmets and protective armor should consider biomechanical tolerances of organs in which they intend to protect and require accurate measurements of deformation as a primary injury metric during impact. To overcome challenges found in velocity and displacement measurements during blunt impact using an integrated accelerometer and two-dimensional (2D) high-speed video, three-dimensional (3D) digital image correlation (DIC) measurements were taken and compared to the accepted techniques. A semispherical impactor was launched at impact velocities from 14 to 20 m/s into synthetic ballistic gelatin to simulate blunt impacts observed in behind armor blunt trauma (BABT), falls, and sports impacts. Repeated measures Analysis of Variance resulted in no significant differences in maximum displacement (p = 0.10), time of maximum displacement (p = 0.21), impact velocity (p = 0.13), and rebound velocity (p = 0.21) between methods. The 3D-DIC measurements demonstrated equal or improved percent difference and low root-mean-square deviation compared to the accepted measurement techniques. Therefore, 3D-DIC may be utilized in BABT and other blunt impact applications for accurate 3D kinematic measurements, especially when an accelerometer or 2D lateral camera analysis is impractical or susceptible to error. [ABSTRACT FROM AUTHOR]

One has to wonder where all the armour from the Middle Ages and the Renaissance that is no longer preserved might have gone. The article presents some forms of repurposing discarded pieces of armour. The focus is on two helms of the fourteenth century, which were secondarily used in a fire hood. The new finds not only tell an interesting story, they are also rare representatives of a once widespread type. [ABSTRACT FROM AUTHOR]

Craniocerebral injuries represent the primary cause of fatalities among riders involved in two-wheeler accidents; nevertheless, the prevalence of helmet usage among these riders remains alarmingly low. Consequently, the accurate identification of riders who are wearing safety helmets is of paramount importance. Current detection algorithms exhibit several limitations, including inadequate accuracy, substantial model size, and suboptimal performance in complex environments with small targets. To address these challenges, we propose a novel lightweight detection algorithm, termed GL-YOLOv5, which is an enhancement of the You Only Look Once version 5 (YOLOv5) framework. This model incorporates a Global DualPooling NoReduction Blend Attention (GDPB) module, which optimizes the MobileNetV3 architecture by reducing the number of channels by half and implementing a parallelized channel and spatial attention mechanism without dimensionality reduction. Additionally, it replaces the conventional convolutional layer with a channel shuffle approach to overcome the constraints associated with the Squeeze-and-Excitation (SE) attention module, thereby significantly improving both the efficiency and accuracy of feature extraction and decreasing computational complexity. Furthermore, we have optimized the Variable Normalization and Attention Channel Spatial Partitioning (VNACSP) within the C3 module of YOLOv5, which enhances sensitivity to small targets through the application of a lightweight channel attention mechanism, substituting it for the standard convolution in the necking network. The Parameter-Free Spatial Adaptive Feature Fusion (PSAFF) module is designed to adaptively modify the weights of each spatial position through spatial pooling and activation functions, thereby effectively enhancing the model's ability to perceive contextual information over distances. Ultimately, GL-YOLOv5 performs remarkably in the custom dataset, achieving a model parameter count of 922,895 M, a computational load of 2.9 GFLOPS, and a mean average precision (mAP) of 92.1%. These advancements significantly improve the model's detection capabilities and underscore its potential for practical applications. [ABSTRACT FROM AUTHOR]

Introduction: In 2022; South Korea had 3.3 million daily bicycle users and around 13,000 crashes with 190 fatalities annually. While helmets are known to prevent head injuries, research on their effectiveness in preventing fatalities is lacking. This study explores factors influencing bicycle-related fatalities and examines if helmets reduce the risk of death in road traffic incidents. Methods: This case-control study used data from the Emergency Department-based Injury In-depth Surveillance (EDIIS) from 2011 to 2021; analyzing 76,983 bicycle injury cases. Of these, 282 fatalities were identified as the case group, and 1,112 controls were randomly selected based on gender, age, and year of visit. The study examined risk factors for bicycle fatalities and used conditional logistic regression to assess the impact of helmet use on traumatic brain injury and in-hospital mortality. Results: In this study of 1,394 patients (282 cases and 1,112 controls), 11.1% were wearing helmets at the time of the crash. The majority of cases involved males (88%) and individuals aged 60-79 years (58.6%). Cases were more likely to occur between 00:00-06:00 and 18:00-00:00 and involved a higher proportion of non-helmeted riders (96.1% vs. 87.1%). Bicycle fatalities were more often due to collisions with automobiles (67.7%), while non-fatal injuries were mainly from crashes without a collision (45.8%). Head injuries were common in both groups, but traumatic brain injury (TBI) was significantly higher among cases (41.5% vs. 11.9%). Key factors associated with ED mortality included the time of injury, alcohol use, crashes on national highways, no helmet use, and collisions with automobiles. Helmet use was associated with a non-significant 35% lower risk of TBI and a significant 63% lower risk of ED mortality. Conclusions: Key risk factors for fatal bicycle injuries included being aged 60-79, male, involved in nighttime crashes, collisions with automobiles, not wearing a helmet, and sustaining a traumatic brain injury (TBI). Helmet use was linked to lower rates of TBIs and reduced mortality. To decrease bicycle-related deaths, stronger legal regulations, educational efforts, and improved infrastructure are essential, along with further interventions and research to effectively tackle these issues. [ABSTRACT FROM AUTHOR]

An enhanced algorithm, YOLOv5s-FCW, is put forward in this study to tackle the problems that exist in the current helmet detection (HD) methods. These issues include having too many parameters, a complex network, and large computation requirements, making it unsuitable for deployment on embedded and other devices. Additionally, existing algorithms struggle with detecting small targets and do not achieve high enough recognition accuracy. Firstly, the YOLOv5s backbone network is replaced by FasterNet for feature extraction (FE), which reduces the number of parameters and computational effort in the network. Secondly, a convolutional block attention module (CBAM) is added to the YOLOv5 model to improve the detection model's ability to detect small objects such as helmets by increasing its attention to them. Finally, to enhance model convergence, the WIoU_Loss loss function is adopted instead of the GIoU_Loss loss function. As reported by the experimental results, the YOLOv5s-FCW algorithm proposed in this study has improved accuracy by 4.6% compared to the baseline algorithm. The proposed approach not only enhances detection concerning small and obscured targets but also reduces computation for the YOLOv5s model by 20%, thereby decreasing the hardware cost while maintaining a higher average accuracy regarding detection. [ABSTRACT FROM AUTHOR]

The rapid adoption of Unmanned Aerial Vehicles (UAVs) in the construction industry has revolutionized safety, surveying, quality monitoring, and maintenance assessment. UAVs are increasingly used to prevent accidents caused by falls from heights or being struck by falling objects by ensuring workers comply with safety protocols. This study focuses on leveraging UAV technology to enhance labor safety by monitoring the use of personal protective equipment, particularly helmets, among construction workers. The developed UAV system utilizes the tensorflow technique and an alert system to detect and identify workers not wearing helmets. Employing the high-precision, high-speed, and widely applicable Faster R-CNN method, the UAV can accurately detect construction workers with and without helmets in real-time across various site conditions. This proactive approach ensures immediate feedback and intervention, significantly reducing the risk of injuries and fatalities. Additionally, the implementation of UAVs minimizes the workload of site supervisors by automating safety inspections and monitoring, allowing for more efficient and continuous oversight. The experimental results indicate that the UAV system's high precision, recall, and processing capabilities make it a reliable and cost-effective solution for improving construction site safety. The precision, mAP, and FPS of the developed system with the R-CNN are 93.1%, 58.45%, and 27 FPS. This study demonstrates the potential of UAV technology to enhance safety compliance, protect workers, and improve the overall quality of safety management in the construction industry. [ABSTRACT FROM AUTHOR]

Purpose: This study explores the protective capabilities of bicycle helmets on serious head injury among bicyclists hospitalized in a Norwegian level 1 trauma centre. Method: Information on helmet use, demographic variables, Abbreviated Injury Scale (AIS) and surgical procedure codes was retrieved from the Oslo University Hospital Trauma Registry for patients with bicycle-related injuries from 2005 through 2016. Outcomes were serious head injury defined as maximum AIS severity score ≥ 3 in the AIS region Head, any cranial neurosurgical procedure, and 30-day mortality. Results: A total of 1256 hospitalized bicyclists were included. The median age was 41 years (quartiles 26–53), 73% were male, 5.3% had severe pre-injury comorbidities, and 54% wore a helmet at the time of injury. Serious head injury occurred in 30%, 9% underwent a cranial neurosurgical procedure, and 30-day mortality was 2%. Compared to non-helmeted bicyclists, helmeted bicyclists were older (43 years, quartiles 27–54, vs. 38 years, quartiles 23–53, p = 0.05), less often crashed during night-time (21% vs. 38%, p < 0.001), less frequently had serious head injury (22% vs. 38%, OR 0.29, 95% CI 0.22–0.39), and less often underwent cranial neurosurgery (6% vs. 14%, OR 0.36, 95% CI 0.24–0.54). No statistically significant difference in 30-day mortality between the two groups was found (1.5% vs. 2.9%, OR 0.50, 95% CI 0.22–1.11). Conclusion: Helmet use was associated with fewer and less severe head injuries and fewer neurosurgical procedures. This adds evidence to the protective capabilities of bicycle helmets. [ABSTRACT FROM AUTHOR]

This multicenter study evaluated the efficacy and safety of a novel cranial remolding helmet (baby band2), which is completely custom-made based on the shape of an infant's cranium. The study included 224 full-term infants from moderate to very severe positional plagiocephaly in Japan. Cranial geometry was assessed before and after helmet therapy using a three-dimensional scanner, and changes in the cranial vault asymmetry index (CVAI) were analyzed. The CVAI improved significantly in all patients, with the most significant improvement observed in the most severely affected group [very severe group: −9.1, severe group: −6.6, moderate group: −4.4 (mean values), p < 0.001]. The group that started therapy before the age of 7 months showed greater improvement compared to those who started therapy at the age of 7 months or older; however, both groups demonstrated significant improvement (<7 months group: −6.6, ≥7 months group: −4.4 (mean values), p < 0.001). No significant differences were observed in therapy efficacy between the centers (p = 0.402) and sex (p = 0.131). During the study period, helmet therapy did not lead to head circumference stunting, and the incidence of redness with baby band2 was five patients (2.2%). This study demonstrated that baby band2 is effective and safe for the therapy of positional plagiocephaly. [ABSTRACT FROM AUTHOR]

It was the aim of the study to analyze the distribution and pattern of facial fractures following e-scooter trauma. Prospective audit data of facial fractures were retrospectively collected to investigate the impact of e-scooter hire, specifically in the form of facial fractures associated with their use. Data collected included patient demographics, mode of injury, date of injury, facial bones involved, presence of soft tissue injury, and factors associated with injury, including intoxication and helmet use. A total of 849 patients were treated for facial fractures during the study period, of which 34 were attributed to e-scooter use. One-half of those injured riding e-scooters were intoxicated, and one-quarter were wearing helmets. There have been an increasing number of facial fractures associated with e-scooter use following the start of the shared e-scooter trial. Zygomaticomaxillary complex fractures were the most common pattern of facial fracture seen. Most patients required surgical management of their injuries. Policymakers should consider how to improve the enforcement of current regulations, given the healthcare cost associated with the management of these preventable injuries. [ABSTRACT FROM AUTHOR]

Ballistic helmets are individual pieces of armor equipment designed to protect a soldier's head from projectiles and fragments. Although very common, these helmets are responsible for several casualties due to their significant back face deformation and low ballistic resistance to projectiles. Therefore, to enhance helmet performance, studies have focused on the development of new materials and new ballistic protection solutions. The purpose of this study was to develop and evaluate a new ballistic solution using thermoplastic-based matrices. The first matrix was based on high-density polyethylene (HDPE). The second matrix was based on HDPE modified with exfoliated montmorillonite (MMT). The main manufacturing processes of a thermoplastic-based ballistic helmet are presented, along with its ballistic performance, according to the National Institute of Justice (NIJ) standard 0106.01 and an investigation of its failure mechanisms via a non-destructive technique. All the helmets resulted in level III-A ballistic protection. The postimpact helmets were scanned to evaluate the back face deformation dimensions, which revealed that the global cone deformation was deeper in the HDPE than in the HDPE/MMT helmet. The failure analysis revealed an overall larger deformation area in the HDPE and HDPE/MMT helmet delamination zones in the regions with a large radius of curvature than in the zones with the lowest radius, which is in accordance with previous simulations reported in the literature. [ABSTRACT FROM AUTHOR]

Enhancing road safety globally is imperative, especially given the significant portion of traffic-related fatalities attributed to motorcycle accidents resulting from non-compliance with helmet regulations. Acknowledging the critical role of helmets in rider protection, this paper presents an innovative approach to helmet violation detection using deep learning methodologies. The primary innovation involves the adaptation of the PerspectiveNet architecture, transitioning from the original Res2Net to the more efficient EfficientNet v2 backbone, aimed at bolstering detection capabilities. Through rigorous optimization techniques and extensive experimentation utilizing the India driving dataset (IDD) for training and validation, the system demonstrates exceptional performance, achieving an impressive detection accuracy of 95.2%, surpassing existing benchmarks. Furthermore, the optimized PerspectiveNet model showcases reduced computational complexity, marking a significant stride in real-time helmet violation detection for enhanced traffic management and road safety measures. [ABSTRACT FROM AUTHOR]

Objective: We examined whether active head aiming with a Helmet Mounted Display (HMD) can draw the pilot's attention away from a primary flight task. Furthermore, we examined whether visual clutter increases this effect. Background: Head up display symbology can result in attentional tunneling, and clutter makes it difficult to identify objects. Method: Eighteen military pilots had to simultaneously perform an attitude control task while flying in clouds and a head aiming task in a fixed-base flight simulator. The former consisted of manual compensation for roll disturbances of the aircraft, while the latter consisted of keeping a moving visual target inside a small or large head-referenced circle. A "no head aiming" condition served as a baseline. Furthermore, all conditions were performed with or without visual clutter. Results: Head aiming led to deterioration of the attitude control task performance and an increase of the amount of roll-reversal errors (RREs). This was even the case when head aiming required minimal effort. Head aiming accuracy was significantly lower when the roll disturbances in the attitude control task were large compared to when they were small. Visual clutter had no effect on both tasks. Conclusion: We suggest that active head aiming of HMD symbology can cause attentional tunneling, as expressed by an increased number of RREs and less accuracy on a simultaneously performed attitude control task. Application: This study improves our understanding in the perceptual and cognitive effects of (military) HMDs, and has implications for operational use and possibly (re)design of HMDs. [ABSTRACT FROM AUTHOR]

Concussion screening among collegiate lacrosse athletes is a major safety priority. Although attention has been directed at concussion management following injury, less is known about the association between cognition and balance during preseason screening. The purpose of the study was to assess the relationship between balance and neurocognition among collegiate male lacrosse players and to examine predictive determinants of postural stability. Participants included a convenience sample of 49 male collegiate Division 3 lacrosse players who completed a demographic survey and performed the immediate postconcussion test (ImPACT) and instrumented Sensory Organization Test (SOT). There was a significant association between balance SOT performance and both verbal memory (r = .59, p < .01) and visual motor speed scores (r = .43, p < .05). Significant correlations between verbal memory and SOT Conditions 2, 5, and 6 were also noted (all p < .05). Verbal memory predicted 33% of the variance in the SOT composite balance score (p < .001). Our results indicate a significant relationship exists between postural stability and both verbal memory and visual processing speed among collegiate male lacrosse players and supports vestibulocortical associations. Findings warrant ongoing performance and executive function tracking and can serve as a conduit for integrated sensorimotor and dual-task training. [ABSTRACT FROM AUTHOR]

The popularity of electric scooters (ES) during the last five years due to climate neutrality and public availability led to increased numbers in traffic accidents with significant injuries. This study was conducted to overview e-scooter related computed tomography (CT) positive traumatic brain injuries, exploring circumstances, clinical course, outcomes and possible relations to behavioral patterns. We retrospectively reviewed medical data of all patients treated in our center during the period 2019 to 2023, medical records were analysed and statistically processed. This review included 45 patients, 75.7% were males and median age was 40 years old. Patient numbers did not differ between weekdays, working days versus weekends and time of the day. Eighty percent of patients were injured from falling off the scooter, the rest were hit by another vehicle while riding. None of the patients were known using helmet, significant alcohol intoxication was found in 68.8% of cases. The most common traumatic intracranial features were subarachnoid hemorrhage (55.6%), followed by brain contusions (48.9%), epidural (26.7%), subdural (26.7%) hemorrhages. Age had a positive correlation with alcohol intoxication (r = 0.596, p = 0.007) and poor outcomes (r = 0.522, p = 0.004), also, men over 40 years old were more likely to undergo surgery (p = 0.024), meanwhile operated patients suffered more infections (p = 0.011) and more often ended with poor outcomes (p < 0.001). [ABSTRACT FROM AUTHOR]

Purpose: Short-track speed skating results in high-energy crashes with an elevated risk of head injury. The goal of this study was to evaluate the resulting kinematics of an anti-rotation helmet technology for speed skating. Methods: Two traditional rigid foam speed-skating helmets (BT and ST) were compared with one anti-rotation speed skating helmet (MIPS). Each helmet was impacted with a pneumatic device across three locations. The resulting linear or rotational accelerations (PLA or PRA) and rotational velocities (PRV) were measured with accelerometers placed on a Hybrid III head form. Additionally, the head impact criterion (HIC) was calculated from accelerations and the brain injury criterion (BrIC) was obtained from rotational velocities. Results: MIPS showed significantly higher values of accelerations (PLA = 111.24 ± 9.21 g and PRA = 8759.11 ± 2601.81 rad/s2) compared with the other helmets at all three impact locations (p < 0.01, ES = 3.00 to 4.11). However, velocities were lowest, but not significantly different, for the MIPS helmet (25.77 ± 1.43 rad/s). Furthermore, all resulting kinematics except peak linear accelerations were significantly different across impact locations. Conclusion: Helmet designs specific to the collision characteristics of speed skating may still be lacking, but would decrease the risk of sport-related concussions. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to determine the impact of standing electric scooters on maxillofacial on the Italian territory. Methods: The authors analyzed the epidemiology of the injuries to define electric mobility's impact on maxillofacial surgery practice. For this retrospective cohort study, data were collected by unifying the standing e-scooter-related fractures database from 10 Italian maxillofacial surgery departments. The reference period considered was from January 2020 to December 2023. The main data considered included age, gender, type of access, time slot of admission, type of admission, alcohol level, helmet use, dynamics of the accident, and area of the fracture. Results: A total of 79 patients were enrolled. The average age of the participants was approximately 31 years. The blood alcohol level was found to be above the Italian norm in 15 cases (19%). Only one patient wore a helmet. The most affected facial third was the middle one with 36 cases (45.5%), followed by the lower one (31, 39.3%). The most recurrent patterns were fractures of the orbito-malar-zygomatic complex (15, 19%), followed by multifocal (bifocal, trifocal) fractures of the mandible (14, 17.5%). Conclusions: This study demonstrated how maxillofacial fractures related to the use of electric scooters are associated with complex patterns, associated with a high rate of post-surgical aftermaths. [ABSTRACT FROM AUTHOR]

To compare traumatic spinal injury patterns between motorcyclists and occupants of other nonheavy motor vehicles using data from the National Spinal Cord and Column Injury Registry of Iran. All drivers/riders and passengers of motorcycles, cars, pick-up trucks, and vans registered between January 2017 to July 2023, met the inclusion criteria for the present study. The logistic regression models were used to compare the patterns of vertebral fracture between the 2 groups. One thousand seven hundred twenty-six spinal fracture patients were identified, 385 (22.3%) motorcyclists and 1341 (77.7%) car occupants with mean ages 33.2 ± 14.3 and 36.1 ± 13.6 years, respectively (P < 0.001). Only 45 (11.7%) motorcyclists used helmets, whereas 856 (63.8%) car occupants used seat belts (P < 0.001). The average numbers of fractured vertebrae were 3.9 ± 1.4 and 3.7 ± 1.1 among car occupants and motorcyclists, respectively (P = 0.004). The proportions of motorcyclists and car occupants with injuries in each spinal region are as follows: lumbar (50.5% of motorcyclists vs. 40.4% of car occupants; P = 0.003), thoracic (39.2% vs. 30.9%; P = 0.01), cervical (24.3% vs. 37.0%; P < 0.001), and sacral (1.3% vs. 7.5%; P < 0.001). The AO Spine type C injuries were present in 6.1% of motorcyclists and 10.1% of car occupants (P = 0.03). Motorcyclists were younger, less educated, had a higher proportion of males, and less commonly used safety devices than car occupants. The most commonly fractured spine region among both groups was the lumbar region. The cervical and sacral vertebrae fractures were significantly more common in car occupants, whereas the thoracic and lumbar vertebrae fractures were significantly more common in motorcyclists. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to describe the outcomes and explore predictors of intubation and mortality in patients with ARDS due to COVID-19 treated with CPAP delivered via a helmet interface and light sedation. Methods: This was a retrospective cohort study involving patients with COVID-19-related ARDS who received CPAP using a helmet developed in Brazil (ELMO™), associated with a light sedation protocol in a pulmonology ward. Demographic, clinical, imaging, and laboratory data, as well as the duration and response to the ELMO-CPAP sessions, were analyzed. Results: The sample comprised 180 patients. The intubation avoidance rate was 72.8%. The lack of necessity for intubation was positively correlated with younger age, > 24-h continuous HELMETCPAP use in the first session, < 75% pulmonary involvement on CT, and ROX index > 4.88 in the second hour. The overall in-hospital mortality rate was 18.9%, whereas those in the nonintubated and intubated groups were 3.0% and 61.2%, respectively. Advanced age increased the mortality risk by 2.8 times, escalating to 13 times post-intubation. Conclusions: ELMO-CPAP with light sedation in a pulmonology ward was successful in > 70% of patients with moderate to severe ARDS due to COVID-19. Younger age, pulmonary involvement, ROX index, and prolonged first Helmet-CPAP session duration were associated with no need for intubation. Older age and intubation are associated with mortality. [ABSTRACT FROM AUTHOR]

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Electric vehicle accidents on the road occur frequently, and head injuries are often the cause of serious casualties. However, most electric vehicle riders seldom wear helmets. Therefore, combining target detection algorithms with road cameras to intelligently monitor helmet-wearing has extremely important research significance. Therefore, a helmet-wearing detection algorithm based on the improved YOLOv8n model, PRE-YOLO, is proposed. First, we add small target detection layers and prune large target detection layers. The sophisticated algorithm considerably boosts the effectiveness of data manipulation while significantly reducing model parameters and size. Secondly, we introduce a convolutional module that integrates receptive field attention convolution and CA mechanisms into the backbone network, enhancing feature extraction capabilities by enhancing attention weights within both channel and spatial aspects. Lastly, we incorporate an EMA mechanism into the C2f module, which strengthens feature perception and captures more characteristic information while maintaining the same model parameter size. The experimental outcomes indicate that in comparison to the original model, the proposed PRE-YOLO model in this paper has improved by 1.3%, 1.7%, 2.2%, and 2.6% in terms of precision P, recall R, mAP@0.5, and mAP@0.5:0.95, respectively. At the same time, the number of model parameters has been reduced by 33.3%, and the model size has been reduced by 1.8 MB. Generalization experiments are conducted on the TWHD and EBHD datasets to further verify the versatility of the model. The research findings provide solutions for further improving the accuracy and efficiency of helmet-wearing detection on complex traffic roads, offering references for enhancing safety and intelligence in traffic. [ABSTRACT FROM AUTHOR]

Due to the material properties of current ski face masks for adolescents, moisture in exhaled air can become trapped within the material fibers and freeze, leading to potential issues such as breathing difficulties and increased risk of facial frostbite after prolonged skiing. This paper proposes a research approach combining computational fluid dynamics (CFD) and ergonomics to address these issues and enhance the comfort of adolescent skiers. We developed head and face mask models based on the head dimensions of 15–17-year-old males. For enclosed cavities, ensuring the smooth expulsion of exhaled air to prevent re-inhalation is the primary challenge. Through fluid simulation of airflow characteristics within the cavity, we evaluated three different inlet configurations. The results indicate that the location of the air inlets significantly affects the airflow characteristics within the cavity. The side inlet design (type II) showed an average face temperature of 35.35 °C, a 38.5% reduction in average CO2 concentration within the cavity, and a smaller vortex area compared to the other two inlet configurations. Although the difference in airflow velocity within the cavity among the three configurations was minimal, the average exit velocity differed by up to 0.11 m/s. Thus, we conclude that the side inlet configuration offers minimal obstruction to airflow circulation and better thermal insulation when used in the design of fully enclosed helmets. This enhances the safety and comfort of adolescent wearers during physical activities in cold environments. Through this study, we aim to further promote the development of skiing education, enhance the overall quality of adolescents' skiing, and thus provide them with more opportunities for the future. [ABSTRACT FROM AUTHOR]

Acrylonitrile-butadiene-styrene (ABS) material is widely used as a protective rigid shell and impact absorber in bike helmets, providing vital protection against head injuries under specific working conditions. However, ABS aging in helmets could affect the safety factor of helmets and shorten the service life. Exploring the transformation during aging process for real assembled helmets made of ABS out shells is crucial for the investigation and fabrication of high performance helmets. Herein, the effect of long-term aging on the physical properties of practical helmets made of ABS outer shells has been discussed systematically. Four different types of helmets were subjected to different aging conditions, i.e., outdoor environment, ultraviolet exposure, hot air, and humid-heat conditions. The impact property and stiffness tests were carried out as a function of aging time and aging conditions. The measured helmets were capable of meeting engineering tolerances when aged under outdoor, ultraviolet, and hot air conditions, and could deliver competitive mechanical performance to their pristine helmets. Yet, after aging under humid-heat for 800 h, the helmets showed an obvious decrease in impact strength, gloss, and stiffness. The influence of different aging conditions was further investigated by thermal and spectral characterizations. The study might provide some valuable advice for helmet performance evaluation. [ABSTRACT FROM AUTHOR]

It is crucial to ensure workers wear safety helmets when working at a workplace with a high risk of safety accidents, such as construction sites and mine tunnels. Although existing methods can achieve helmet detection in images, their accuracy and speed still need improvements since complex, cluttered, and large-scale scenes of real workplaces cause server occlusion, illumination change, scale variation, and perspective distortion. So, a new safety helmet-wearing detection method based on deep learning is proposed. Firstly, a new multi-scale contextual aggregation module is proposed to aggregate multi-scale feature information globally and highlight the details of concerned objects in the backbone part of the deep neural network. Secondly, a new detection block combining the dilate convolution and attention mechanism is proposed and introduced into the prediction part. This block can effectively extract deep features while retaining information on fine-grained details, such as edges and small objects. Moreover, some newly emerged modules are incorporated into the proposed network to improve safety helmet-wearing detection performance further. Extensive experiments on open dataset validate the proposed method. It reaches better performance on helmet-wearing detection and even outperforms the state-of-the-art method. To be more specific, the mAP increases by 3.4%, and the speed increases from 17 to 33 fps in comparison with the baseline, You Only Look Once (YOLO) version 5X, and the mean average precision increases by 1.0% and the speed increases by 7 fps in comparison with the YOLO version 7. The generalization ability and portability experiment results show that the proposed improvements could serve as a springboard for deep neural network design to improve object detection performance in complex scenarios. [ABSTRACT FROM AUTHOR]

Objectives: Plagiocephaly is a flattening or asymmetry of the skull in infants that –while benign– can be distressing to parents. There are no standardized treatment recommendations, but helmeting therapy (HT) can be pursued. However, there is no strong evidence for the effectiveness of HT, leading to ambiguity for who should be offered this intervention. In this study, we aim to evaluate any differences in the proportion of patients being offered HT based on race/ethnicity, sex, or insurance type. Methods: A retrospective review from January 12th, 2017, to April 30th, 2022, of all patients with a plagiocephaly diagnosis under 18 months of age was conducted. A one-way analysis of variance was used to assess significance with differences <0.05 considered significant. Results: Of the 1667 patients identified with plagiocephaly, 807 (48.4%) patients were offered HT, and 501 (30.1%) subsequently received a helmet. Patients with public insurance represented a significantly lower proportion of patients offered HT compared to their respective proportion within all patients diagnosed with plagiocephaly (26.9% vs 31.8%, P =.01). Additionally, patients who identified as Black or African American represented a significantly lower proportion of patients offered HT compared to their respective proportion within all patients diagnosed with plagiocephaly (8.1% vs 10.6%, P =.04). Conclusion: Our study demonstrates that the proportions of patients with plagiocephaly who were offered HT compared to their overall proportion within all patients diagnosed with plagiocephaly were different for patients with public insurance and patients who identified as Black or African American. This highlights the need for standardized recommendations for HT. [ABSTRACT FROM AUTHOR]

ABSTRACT:Motorized two-wheeler users account for 45% of road fatalities in 2021 in India. Correct helmet use decreases the risk of fatalities, but information about the prevalence of correct helmet use is limited in the Indian context. This study aims to assess the prevalence of helmet use and factors associated with correct helmet use among motorized two-wheeler users in Bengaluru city, India. This observational cross-sectional assessment was conducted in a random-representative sample of 98021 motorized two-wheelers sampled from 15 intersections. Helmet use and other information were collected by trained Field Data Collectors via hand-held tablet devices and the KoBo collect application, following a globally used checklist. The prevalence of helmet use (all types) was 88% among riders and pillion together and 92.4% among riders. However, the prevalence of correct helmet use is 38% among riders, and non-standard helmet use is 27%. This study reveals a correct helmet use gap in Bengaluru city. The study recommends the need to shift enforcement, messaging, and intervention focus towards correct helmet use and the implementation of routine population-based surveillance for helmet use in the city. [ABSTRACT FROM AUTHOR]

Brain injuries in warfighters due to low-level blasts, even while wearing a helmet, are common. Understanding how the form of a shock wave changes when impacting a head donning a helmet may present solutions to reducing shock loading on the head, thereby reducing the prevalence of blast-induced traumatic brain injury. A manikin with PCB piezoelectric transducers throughout the head was exposed to low-pressure free-field blasts using an RDX-based explosive charge designed to output a side-on overpressure of 4 pounds per square inch (psi) [27.5 kilopascals (kPa)] with and without a helmet. Orientations of 0, 45, 90, 135, and 180 degrees were evaluated to observe changes in overpressure versus time (p(t)) waveforms. The waveforms were compared to schlieren imagery in which a shock wave impacted 3D-printed silhouettes of a warfighter donning a helmet, showing shock wave flow under the helmet at 0-, 90-, and 180-degree orientations. It was found that trapped shock waves under the helmet create regions of high overpressure and increase the duration of exposure, resulting in higher impulses imparted onto the head. While wearing a helmet, the 90-degree orientation resulted in the greatest reduction in overall peak overpressure, with an 8% decrease compared to the 0-degree orientation. In contrast, the 180-degree orientation led to an increase by 30%. For impulse, the 90-degree orientation showed the greatest reduction, with a decrease of 21%. The 0-degree orientation had the highest overall impulse among all orientations when wearing a helmet. [ABSTRACT FROM AUTHOR]

Horseback riding can cause severe brain and spinal injuries. This study aimed to identify the spectrum of neurosurgical injuries related to recreational horseback riding. A retrospective study was performed utilizing the University of Puerto Rico neurosurgery database to identify patients who were consulted to the neurosurgery service between 2018 and 2023 after a horse fall during recreational activities. The outcome upon discharge using the modified Rankin scale (mRS) was documented. Descriptive statistics were used to report frequency and median values. The neurosurgery service evaluated and managed 112 patients with a horseback riding fall-related injury during 6 years. Ninety-eight (87.5%) patients were male. The patients' median age was 31.5 (IQR 22–40). There were 89 head injuries (79.5%), 19 spinal injuries (17%), and 4 combined head/spine injuries (3.5%). Forty percent of the patients were admitted to inpatient care with a median length of stay of 7 days (IQR 3–17). Twenty-four patients (21%) required surgery. Upon discharge, 86.6% of the patients had an mRS grade of 0–2, 3.6% had a grade of 3, 1.8% had a grade of 4, and 1.8% had a grade of 5. Seven patients (6%) died (mRS grade 6). Most neurologic injuries involve isolated trauma to the head. Fifteen percent of the riders' falls were caused after the horse was impacted by a motor vehicle. Forty percent of the patients require admission and 21% undergo surgery. Ten percent of the patients had a poor mRS grade of 4– to 6 when discharged. [ABSTRACT FROM AUTHOR]

Traumatic injury is responsible for eight million childhood deaths annually. In Uganda, there is a paucity of comprehensive data describing the burden of pediatric trauma, which is essential for resource allocation and surgical workforce planning. This study aimed to ascertain the burden of non-adolescent pediatric trauma across four Ugandan hospitals. We performed a descriptive review of four independent and prospective pediatric surgical databases in Uganda: Mulago National Referral Hospital (2012-2019), Mbarara Regional Referral Hospital (2015-2019), Soroti Regional Referral Hospital (SRRH) (2016-2019), and St Mary's Hospital Lacor (SMHL) (2016-2019). We sub-selected all clinical encounters that involved trauma. The primary outcome was the distribution of injury mechanisms. Secondary outcomes included operative intervention and clinical outcomes. There was a total of 693 pediatric trauma patients, across four hospital sites: Mulago National Referral Hospital (n = 245), Mbarara Regional Referral Hospital (n = 29), SRRH (n = 292), and SMHL (n = 127). The majority of patients were male (63%), with a median age of 5 [interquartile range = 2, 8]. Chiefly, patients suffered blunt injury mechanisms, including falls (16.2%) and road traffic crashes (14.7%) resulting in abdominal trauma (29.4%) and contusions (11.8%). At SRRH and SMHL, from which orthopedic data were available, 27% of patients suffered long-bone fractures. Overall, 55% of patients underwent surgery and 95% recovered to discharge. In Uganda, non-adolescent pediatric trauma patients most commonly suffer injuries due to falls and road traffic crashes, resulting in high rates of abdominal trauma. Amid surgical workforce deficits and resource-variability, these data support interventions aimed at training adult general surgeons to provide emergency pediatric surgical care and procedures. [ABSTRACT FROM AUTHOR]

This paper presents here a novel electrical sensor for detecting alcohol concentration in the exhale of an individual. We highlight fabrication of the sensor followed by subsequent assemblage into a handheld unit. The prototype yields a remarkable sensitivity along with a linear range of ~ 250–800 ppm. Additionally, we demonstrate the implementation of it in the helmet of a biker—which is further validated by in situ results related to monitoring exhale activity of few subjects. Through proper tuning with the ignition control system, the prototype can act as a protective gear for drunken drivers. Once the concentration of alcohol is sensed above a permissible level, the ignition system can be momentarily stopped; thereby averting plausible accidents. We believe that this sensor can be upgraded to more advanced protocol via a little tweaking with Internet of Things. [ABSTRACT FROM AUTHOR]

Sarcopenia is a disease in which a decline in muscle mass with age is associated with a decline in physical performance. In the field of otorhinolaryngology, head and neck surgery, sarcopenia is gaining attention as a cause of swallowing disorders and as a problem in the treatment of head and neck cancer. Head and neck cancer occurs in anatomical sites related to swallowing, so patients with head and neck cancer are prone to swallowing disorders and "nutrition-related sarcopenia." Since it is a cancer, it also becomes a "disease-related sarcopenia," making it easy for patients to develop secondary sarcopenia. Medical intervention against sarcopenia is important in order to decrease the number of adverse events related to treatments for cases with sarcopenia, with reports stating that proactive exercise and nutritional therapy prior to treatment for cases with sarcopenia contributes to a decrease in serious complications as well as improving the survival rate. It is the same for head and neck cancer patients with sarcopenia, so intervention prior to treatment of head and neck cancer is an area that is expected to see reports in the future. However, if the disease is malignant, it is highly likely that sarcopenia cannot be sufficiently improved due to the short period of time from diagnosis to the beginning of treatment. In this case, choosing a treatment that takes sarcopenia into consideration is another way to handle it. Assessing sarcopenia prior to treatment may help avoid post-treatment pneumonia related to sarcopenia, postoperative complications including fistula, radiation-induced toxicity including swallowing disorders, and chemotherapy-related toxicity, and it is believed to greatly contribute to the prognosis of the overall survival (OS), disease-free survival (DFS), and disease-specific survival (DSS). [ABSTRACT FROM AUTHOR]

Employ a novel testing method to assess Multi Directional Impact Protection System (MIPS) helmet technology on rotational velocity and acceleration during head impact. An optimization study was completed utilizing a 50th percentile male Hybrid III anthropomorphic test device (ATD). Helmets included expanded polystyrene foam (EPS) and two different MIPS helmets (MIPS 1, MIPS 2). A 24.38-m-long elevated track with rails and a motorized sled was utilized to replicate a fall from approximately 2.13 m. The sled was set to a speed of 20.92 kph, where a tripping mechanism induced rotation in the ATD from the sled and onto a sand surface. During impact of the ATD with the sand surface, head kinematics were measured using resultant acceleration (peak G's), duration of impact (ms), and rotational velocity (rad/s). A total of three trials for each helmet did not demonstrate a significant difference between the EPS vs. MIPS 1 group with, peak (G's) for resultant acceleration (p = 0.100), duration (ms) for resultant acceleration, (p = 0.100), peak (G's) for rotational velocity, (p = 0.700), and duration (ms) for rotational velocity (p = 0.700). Similarly, the EPS vs. MIPS 2 testing demonstrated no significant differences between the MIPS 2 helmet compared to the EPS helmet, with resultant acceleration (p = 0.400), duration acceleration (p = 0.200), rotational velocity (p = 0.400) and duration velocity (p = 0.400). However, when the MIPS helmet data were pooled, and the EPS helmet data were compared, a statistically significant difference in the duration of acceleration was found (p = 0.048). Current testing uses a helmeted head form which is dropped or rolled from a prescribed height. These methods discount the loading placed on the neck and head through the angular momentum of the body. Our novel testing method did not find significant differences between the helmet types in diminishing peak rotational forces to the brain; however, our data suggests that MIPS helmet liners may reduce duration of impact. The reduction of acceleration duration could indicate less rotation of the neck, due to the dampening of these forces by the MIPS liners. [ABSTRACT FROM AUTHOR]

Background: The percentage of elderly trauma patients under anticoagulation and antiplatelet agents has been rising lately. As newer agents are introduced, each comes with its own advantages and precautions. Our study covered elderly patients admitted to the ED with maxillofacial trauma while on anticoagulation (AC) or antiplatelet therapy (APT). We aimed to investigate the demographic characteristics, causes, and types of maxillofacial trauma, along with concomitant injuries, duration of hospitalisation, haemorrhagic complications, and the overall costs of care in the emergency department (ED). Methods: Data were gathered from the ED of Bern University Hospital. In this retrospective analysis, patients over 65 of age were included, who presented at our ED with maxillofacial trauma between 2013 and 2019 while undergoing treatment with therapeutic AC/APT. Results: The study involved 188 patients with a median age of 81 years (IQR: 81 [74; 87]), of whom 55.3% (n=104) were male. More than half (54.8%, n=103) were aged 80 years or older. Cardiovascular diseases were present in 69.7% (n=131) of the patients, with the most common indications for AC/APT use being previous thromboembolic events (41.5%, n=78) and atrial fibrillation (25.5%, n=48). The predominant cause of facial injury was falls, accounting for 83.5% (n=157) of cases, followed by bicycle accidents (6.9%, n=13) and road-traffic accidents (5.3%, n=10). The most common primary injuries were fractures of the orbital floor and/or medial/lateral wall (60.1%, n=113), zygomatic bone (30.3%, n=57), followed by isolated orbital floor fractures (23.4%, n=44) and nasal bone fractures (19.1%, n=36). Fractures of the mandible occurred in 14.9% (n=28). Facial hematomas occurred in 68.6% of patients (129 cases), primarily in the midface area. Relevant facial bleeding complications were intracerebral haemorrhage being the most frequent (28.2%, n=53), followed by epistaxis (12.2%, n=23) and retrobulbar/intraorbital hematoma (9%, n=17). Sixteen patients (8.5%) experienced heavy bleeding that required emergency treatment. The in-hospital mortality rate was 2.1% (4 cases). Conclusions: This study indicates that falls are the leading cause of maxillofacial trauma in the elderly, with the most common diagnoses being orbital, zygomatic, and nasal fractures. Haemorrhagic complications primarily involve facial hematomas, especially in the middle third of the face, with intracerebral haemorrhage being the second most frequent. Surgical intervention for bleeding was required in 8.5% of cases. Given the aging population, it is essential to improve prevention strategies and update safety protocols, particularly for patients on anticoagulant/antiplatelet therapy (AC/APT). This can ensure rapid diagnostic imaging and prompt treatment in emergencies. [ABSTRACT FROM AUTHOR]

Autonomous outdoor moving objects like cars, motorcycles, bicycles, and pedestrians present different risks to the safety of Visually Impaired People (VIPs). Consequently, many camera-based VIP mobility assistive solutions have resulted. However, they fail to guarantee VIP safety in practice, i.e., they cannot effectively prevent collisions with more dangerous threats moving at higher speeds, namely, Critical Moving Objects (CMOs). This paper presents the first practical camera-based VIP mobility assistant scheme, ARAware, that effectively identifies CMOs in real-time to give the VIP more time to avoid danger through simultaneously addressing CMO identification, CMO risk level evaluation and classification, and prioritised CMO warning notification. Experimental results based on our real-world prototype demonstrate that ARAware accurately identifies CMOs (with 97.26% mAR and 88.20% mAP) in real-time (with a 32 fps processing speed for 30 fps incoming video). It precisely classifies CMOs according to their risk levels (with 100% mAR and 91.69% mAP), and warns in a timely manner about high-risk CMOs while effectively reducing false alarms by postponing the warning of low-risk CMOs. Compared to the closest state-of-the-art approach, DEEP-SEE, ARAware achieves significantly higher CMO identification accuracy (by 42.62% in mAR and 10.88% in mAP), with a 93% faster end-to-end processing speed. [ABSTRACT FROM AUTHOR]

BACKGROUND: Wearing protective helmets is an important prevention strategy to reduce work-related traumatic brain injuries. The existing standardized testing systems are used for quality control and do not provide a quantitative measure of the helmet performance. OBJECTIVE: To analyze the failure characterizations of Type I industrial helmets and develop a generalized approach to quantify the shock absorption performance of Type I industrial helmets based on the existing standardized setups. METHODS: A representative basic Type I construction helmet model was selected for the study. Top impact tests were performed on the helmets at different drop heights using two different impactor masses (3.6 and 5.0 kg). RESULTS: When the helmets were impacted with potential impact energies smaller than the critical potential impact energy values, there was a consistent relationship between the peak impact force and the potential impact energy. When the helmets were impacted under potential impact energies greater than the critical potential impact energy values, the peak impact forces increased steeply with increasing potential impact energy. CONCLUSION: A concept of safety margin for construction helmets based on potential impact energy was introduced to quantify the helmets' shock absorption performance. The proposed method will help helmet manufacturers improve their product quality. [ABSTRACT FROM AUTHOR]

Purpose: To provide additional information on optimal start times and therapeutic effectiveness based on treatment outcome of Japanese infants with positional plagio- and brachycephaly (PPB) receiving cranial molding helmet therapy (CMHT). Methods: In this retrospective cohort study, data from a 3D head scanning system was analyzed from 2173 Japanese infants who completed CMHT. Anterior and posterior symmetry ratio (ASR and PSR) and longitudinal to transverse diagonal ratios (LD/TDR) were calculated based on skull shape at helmet design and at completion of therapy. The outcomes were evaluated using the regression analysis and a predictive model using cranial parameters was developed. Results: The earlier the start of therapy, the greater the therapeutic effect on ASR, PSR, and LD/TDR (ASR, −0.134 percent points (ppt)/day; PSR, −0.086 ppt/day; and LD/TDR, −0.131 ppt/day). In the predictive model, in addition to starting age of the therapy, sex (male), the degree of deformity of the head (DoD) (moderate and severe), quadrant volume, PSR, and head circumference at the start of treatment also had a positive effect on changes in ASR, DoD (moderate and severe), ASR, LD/TDR and transverse diameter for PSR, sex (male), DoD (moderate), quadrant volume, PSR, and head circumference for LD/TDR. Conclusion: The starting age of therapy had a relatively smaller contribution to outcome effects. Applying the cranial parameter obtained at the start of treatment to the predictive model helps to predict the effect of CMHT and whether PPB can be treated with CMHT in infants of older age. [ABSTRACT FROM AUTHOR]

Positional plagiocephaly is a deformational cranial flattening frequently treated in pediatric neurosurgical practice. Positional maneuvers and orthotic helmet therapy are preferred therapeutic options for moderate-to-severe forms. Treatment response seems to be age-dependent. Nevertheless, predictive data are vague, and cost-efficiency might be a limiting factor for treatment. The purpose of this study was to investigate the early predictive value of sonographic parameters on the efficacy of orthotic helmet therapy through the assessment of changes in skull shape and correlation of the parameters with caliper cephalometry values and with age. A consecutive cohort of 49 patients < 10 months of age, undergoing orthotic helmet therapy for positional plagiocephaly, was recruited prospectively. The authors routinely assessed the patency of the lambdoid sutures by ultrasound and the following additional skull parameters were measured: suture width, adjacent full bone thickness, adjacent cortical bone thickness and occipital angle. Caliper cephalometric values, as well as demographic and clinical data were collected. Retrospective data analysis showed an inverse relation between both cortical and full skull bone thickness and early treatment efficacy, defined by a reduction in the occipital angle. The improvement of sonographic parameters correlated with the development of cranial caliper cephalometry values. In conclusion, the sonographic assessment of skull bone thickness is a safe and cost-effective tool to predict the early efficacy of orthotic helmet therapy in positional plagiocephaly and might, therefore, help the clinician to foresee the potential evolution of the deformity. [ABSTRACT FROM AUTHOR]

Head injuries resulting from e-scooter use have led to calls for helmet use to be promoted or mandatory. Helmet use is mandatory for e-scooters in Australia but observational studies have reported significant levels of nonuse, particularly by riders of shared e-scooters. The aim of this study is to understand whether nonuse in the mandatory context is a consistent behavior for an individual or is situationally-influenced, and what are the factors associated with nonuse. An online survey was completed between 2022 and 2023 by 360 adult e-scooter riders in Canberra, Australia. Riders were asked whether they had worn a helmet on their last ride and how often they had not worn a helmet when riding in the last 30 days. The survey also asked about rider characteristics (demographics, frequency of e-scooter and bicycle use, perceived risk of e-scooter use, e-scooter ownership, and risky behaviors while riding), trip duration and perceptions of the helmet requirement (knowledge of and support for the law). Respondents were mostly male, young, highly educated, and full-time workers. Of the 29.1% of riders who reported riding without a helmet in the last 30 days, 24.4% had worn a helmet at least once during that period and 4.8% had consistently not worn a helmet. Younger age, shared e-scooter use and more frequent riding frequency (shared e-scooters only) were associated with helmet nonuse in the bivariate analyses but not in the logistic regression. Logistic regression showed that the independent predictors of helmet nonuse were the number of risky riding behaviors, lack of knowledge, and lack of support for the law. Most nonuse of helmets in a mandatory context seems to be situational, rather than consistent. Many of the factors associated with nonuse of helmets for e-scooters are similar to those reported for bicycles. Nonuse of helmets appears to be one of a number of risky behaviors performed by riders, rather than being primarily an outcome that is specific to factors associated with helmets (e.g., concerns about hygiene, discomfort or availability). [ABSTRACT FROM AUTHOR]

Electric power operation, as one of the key fields in the world, faces particularly prominent safety issues. Ensuring the safety of operators has become the most fundamental requirement in power operation. However, there are some safety hazards in power construction. These hazards are mainly due to weak safety awareness among staff and the failure to standardize the wearing of safety helmets. In order to effectively address this situation, technical means such as video surveillance technology and computer vision technology can be utilized to monitor whether staff are wearing helmets and provide timely feedback. Such measures will greatly enhance the safety level of power operation. This paper proposes an improved lightweight helmet detection algorithm named YOLO-M3C. The algorithm first replaces the YOLOv5s backbone network with MobileNetV3, successfully reducing the model size from 13.7 MB to 10.2 MB, thereby increasing the model's detection speed from 42.0 frames per second to 55.6 frames per second. Then, the CA attention mechanism is introduced into the backbone network to enhance the feature extraction capability of the model. Finally, in order to further improve the detection recall rate and accuracy of the model, a knowledge distillation of the model was carried out. The experimental results show that, compared with the original YOLOv5s algorithm, the average accuracy of the improved YOLO-M3C algorithm is improved by 0.123, and the recall rate is the same. These results verify that the algorithm YOLO-M3C has excellent performance in target detection and recognition, which can improve accuracy and confidence, while reducing false detection and missing detection, and effectively meet the needs of helmet-wearing detection. [ABSTRACT FROM AUTHOR]