Profile of low and middle-income countries with increases versus decreases in road crash fatality population rates and necessity of motorcycle safety

INTRODUCTION

Road crash fatalities have increased significantly in Low- and Middle- Income Countries (LMICs) between 2006 and 2016. This study presents how road safety characteristics have changed in LMICs by comparing data over time and relationships between the road crash fatality increase and a wide range of data from LMICs. Parametric and nonparametric methods are used to test significance.

METHOD

There were 35 countries in the Latin America and Caribbean region, the Sub-Saharan Africa region, the East Asia and Pacific region, and the South Asia region, where the population rate of road crash fatalities consistently increased as per country reports, World Health Organization and Global Burden of Disease estimates. In these countries, the proportion of fatalities involving motorcycles (including powered two or three-wheelers) substantially increased (44%) over the same time (statistically significant). In these countries, the helmet-wearing rate was only 46% for all passengers. These patterns were not observed in LMICs with decreasing population fatality rates.

RESULTS

Motorcycle helmet usage rates strongly correlate with decreasing fatalities per 10,000 motorcycles in Low-Income Countries (LICs) and LMICs. Effective interventions (including increasing helmet usage) are urgently needed for motorcycle crash trauma in LMICs, especially where the economy and motorization rapidly grow. National strategies for motorcycle safety, conforming to the Safe System principles, are recommended.

CONCLUSIONS

For evidence-based policy formulation, there is a need to continue strengthening data collection, sharing, and use.

Helmet-Mounted Real-Time Toxic Gas Monitoring and Prevention System for Workers in Confined Places

Occupational health and safety hazards associated with confined places are mainly caused by exposure to toxic gases and oxygen deficiency. Lack of awareness, inappropriate monitoring, and improper evacuation methods can lead to worker fatalities. Although previous studies have attempted to develop systems to solve this issue, limited research is available on their application in confined places. In this study, a real-time helmet-mounted system was developed to monitor major toxic gases (methane (CH₄), hydrogen sulfide (H₂S), ammonia (NH₃), and carbon monoxide (CO)), oxygen, temperature, and humidity. Workers outside and inside confined spaces receive alerts every second to immediately initiate the rescue operation in the event of a hazard. The test results of a confined environment (wastewater treatment unit) highlighted that concentrations of CH₄ and H₂S were predominant (13 ppm). Compared to normal atmosphere, CH₄ concentration was 122- and 130-fold higher in the landfill and digestion tanks, respectively, while H₂S was 36- and 19-fold higher in the primary and secondary clarifiers, respectively. The oxygen content (18.2%) and humidity (33%) were below the minimum required limits. This study will benefit future research to target appropriate toxic gas monitoring and alert workers by studying the existing issues and associated factors in confined places.

Unhelmeted Riding, Drunk Riding, and Unlicensed Riding among Motorcyclists: A Population Study in Taiwan during 2011-2016

This study aimed to investigate the association between drunk riding, unhelmeted riding, unlicensed riding, and running-off-road (ROR) crashes. Multiple logistic regression was used to calculate the adjusted odds ratio (AOR) by using the National Taiwan Traffic Crash Dataset for 2011-2016. The results revealed that unhelmeted riding was associated with 138% (AOR = 2.38; CI (confidence interval) = 2.34-2.42) and 47% (AOR = 1.47; CI = 1.45-1.49) higher risks of drunk riding and unlicensed riding, respectively. The risk of unhelmeted riding increased with blood alcohol concentrations (BACs), and riders with the minimum BAC (0.031-0.05%) had nearly five times (AOR = 4.99; CI = 4.74-5.26) higher odds of unlicensed riding compared with those of riders with a negative BAC. Unhelmeted riding, drunk riding, and unlicensed riding were associated with 1.21 times (AOR = 1.21; CI = 1.13-1.30), 2.38 times (AOR = 2.38; CI = 2.20-2.57), and 1.13 times (AOR = 1.13; CI = 1.06-1.21) higher odds of ROR crashes, respectively. The three risky riding behaviours (i.e., unhelmeted riding, drunk riding, and unlicensed riding) were significantly related to ROR crashes. The risk of unhelmeted riding and ROR crashes increased with BACs.

Relationship between the use and types of helmets with facial injuries - a prospective study

INTRODUCTION

many studies have demonstrated the benefits of helmet to prevent and reduce severity of injuries in motorcyclists.

OBJECTIVE

the aim of the present study was to evaluate a possible relationship between the use of different types of helmets and the occurrence of facial injuries among victims of motorcycle accidents, seen at Hospital da Restauração, Recife/PE, Brazil.

MATERIALS AND METHODS

demographic and trauma data were collected from hospitalized motorcycle accident victims with facial injuries from December 2020 to July 2021. Pearsons chi-square test was used to assess association between two categorical variables using a margin of error of 5%.

RESULTS

among the participants, the average age was 33.46 years. The age group between 18 and 29 years was the most prevalent. Most participants were male. 60.0% of motorcyclists used helmets at the time of the accident and of this percentage 37.6% used fixed full-face helmet, 16.5% open-face helmet and the other 5.9% articulated full-face helmet. 62.7% of participants had facial fractures. Among the fractures, those of the zygomatic-orbital complex were the most common fracture and were significantly associated with the use of helmets, especially with open-face helmet.

CONCLUSIONS

the use of helmets was associated with a lower number of facial fractures among patients who were victims of motorcycle accidents. Fracture of the zygomatic-orbital complex was related to the absence of a helmet at the time of the accident, as well as the use of open-face helmets.

The effects of whole-body vibration and head supported mass on performance and muscular demand

For military rotary-wing aircrew, little is known about the interactive effects of vibration exposure and the addition of head supported mass (HSM) on target acquisition performance, head kinematics, and muscular demand. Sixteen healthy male participants wore an aviator helmet with replica night vision goggles and completed rapid aiming head movements to acquire visual targets in axial and off-axis movement trajectories while secured in a Bell-412 helicopter seat mounted to a human-rated shaker platform. HSM configuration (with or without a counterweight (CW)) and vertical whole-body vibration (WBV) conditions (vibration or no vibration exposure) were manipulated as independent variables. WBV exposure degraded target acquisition performance and lengthened time to peak velocity of head movements. For yaw peak velocity in the axial movement trajectory, peak velocity was 9.9%, 11.6%, and 8.4% higher in the noCW + WBV condition compared to the CW + WBV, CW + noWBV, and noCW + noWBV conditions, respectively.Practitioner summary: The majority of military helicopter aircrew use a counterweight to counteract the anteriorly displaced load of night vision googles. This study was undertaken to better understand how helicopter vibration and counterweight use interactively affect performance and health-related measures during rapid scanning head movements.

Helmet Wearing State Detection Based on Improved Yolov5s

At many construction sites, whether to wear a helmet is directly related to the safety of the workers. Therefore, the detection of helmet use has become a crucial monitoring tool for construction safety. However, most of the current helmet wearing detection algorithms are only dedicated to distinguishing pedestrians who wear helmets from those who do not. In order to further enrich the detection in construction scenes, this paper builds a dataset with six cases: not wearing a helmet, wearing a helmet, just wearing a hat, having a helmet, but not wearing it, wearing a helmet correctly, and wearing a helmet without wearing the chin strap. On this basis, this paper proposes a practical algorithm for detecting helmet wearing states based on the improved YOLOv5s algorithm. Firstly, according to the characteristics of the label of the dataset constructed by us, the K-means method is used to redesign the size of the prior box and match it to the corresponding feature layer to increase the accuracy of the feature extraction of the model; secondly, an additional layer is added to the algorithm to improve the ability of the model to recognize small targets; finally, the attention mechanism is introduced in the algorithm, and the CIOU_Loss function in the YOLOv5 method is replaced by the EIOU_Loss function. The experimental results indicate that the improved algorithm is more accurate than the original YOLOv5s algorithm. In addition, the finer classification also significantly enhances the detection performance of the model.

A Fiber-Optic Sensor-Embedded and Machine Learning Assisted Smart Helmet for Multi-Variable Blunt Force Impact Sensing in Real Time

Early on-site diagnosis of mild traumatic brain injury (mTBI) will provide the best guidance for clinical practice. However, existing methods and sensors cannot provide sufficiently detailed physical information related to the blunt force impact. In the present work, a smart helmet with a single embedded fiber Bragg grating (FBG) sensor is developed, which can monitor complex blunt force impact events in real time under both wired and wireless modes. The transient oscillatory signal "fingerprint" can specifically reflect the impact-caused physical deformation of the local helmet structure. By combination with machine learning algorithms, the unknown transient impact can be recognized quickly and accurately in terms of impact magnitude, direction, and latitude. Optimization of the training dataset was also validated, and the boosted ML models, such as the S-SVM+ and S-IBK+, are able to predict accurately with complex databases. Thus, the ML-FBG smart helmet system developed by this work may become a crucial intervention alternative during a traumatic brain injury event.

Smart Helmet-Based Proximity Warning System to Improve Occupational Safety on the Road Using Image Sensor and Artificial Intelligence

Recently, collisions between equipment and workers occur frequently on the road in construction and surface mining sites. To prevent such accidents, we developed a smart helmet-based proximity warning system (PWS) that facilitates visual and tactile proximity warnings. In this system, a smart helmet comprising an Arduino Uno board and a camera module with built-in Wi-Fi was used to transmit images captured by the camera to a smartphone via Wi-Fi. When the image was analyzed through object detection and a heavy-duty truck or other vehicle was detected in an image, the smartphone transmitted a signal to the Arduino via Bluetooth and, when a signal was received, an LED strip with a three-color LED visually alerted the worker and the equipment operator. The performance of the system tested the recognition distance of the helmet according to the pixel size of the detected image in an outdoor environment. The proposed personal PWS can directly produce visual proximity warnings to both workers and operators enabling them to quickly identify and evacuate from dangerous situations.

Web content mining analysis of e-scooter crash causes and implications in Germany

In Germany, police reports published via press are neither uniformly written nor accessible to the public. There is a lack of comprehensive and factual data-based analyses of e-scooter crashes and their causes. We collected 1936 crash-related reports over two years via the German press portal based on a systematic web content mining process. Sentiment analysis results revealed that the police reports' coverage is predominantly factual and neutral and, therefore, useful for keyword-based analyses. After identifying the 46 most relevant keywords in the reports, we generated an adjacency matrix to investigate the keywords' dependencies, visualized the network and dependencies of the most relevant keywords, and categorized them into four thematic clusters using the Louvain algorithm. Our results and findings reveal that driving under drug influence, especially alcohol, is one serious problem. Riding e-scooter in pairs and on forbidden terrain or in the wrong direction are also common causes of crashes. Consequences for e-scooter riders are severe injuries, driving license revocation, fines, criminal charges, and incurring for property damage. Further, wearing protective gear and helmets is of low acceptance among the e-scooter ridership. Based on our results and findings, we recommend e-scooter bans during the night times for some locations, obligatory driving tests before first e-scooter use, and helmet wearing.

Prediction of Helmet Use Behavior among Motorcyclists Based on the Theory of Planned Behavior

BACKGROUND

Road traffic injuries (RTIs) are one of the most critical factors that endanger human health. More specifically, head and neck injuries are the main causes of deaths and disabilities among motorcyclists. This study aimed to investigate the predictive factors of helmet use behavior among motorcyclists based on the theory of planned behavior (TPB).

STUDY DESIGN

This study followed the cross-sectional design.

METHODS

This study was conducted on randomly selected 730 motorcyclist employees in Qom, Iran, in 2021. The data collection tool was a self-administered researcher-made questionnaire, including items on demographic characteristics, history of RTIs, and constructs of TPB. Data were analyzed using descriptive summary statistics, analysis of variance, independent samples t test, Pearson correlation coefficient, and structural equation modeling (SEM).

RESULTS

In this study, only 9.8% of the participants reported that they always used a helmet while riding a motorcycle. About 60% reported a history of a motorcycle crash, and 11.5% had a history of head injuries. The direct effect of attitude, subjective norms, and perceived behavioral control on the intention to use a helmet were statistically significant, explaining 59% of the variation in behavioral intention (intention to use a helmet) (R2=0.59). Moreover, perceived behavioral control and behavioral intention had significant effects on helmet use behavior (R2=0.26).

CONCLUSION

The prevalence of helmet use among the studied population was very low. Moreover, TPB was useful in identifying the determinants of behavior and especially behavioral intention of helmet use among motorcyclists.

Development of detailed finite element models for in silico analyses of brain impact dynamics

BACKGROUND AND OBJECTIVE

In the last few decades, several studies have been performed to investigate traumatic brain injuries (TBIs) and to understand the biomechanical response of brain tissues, by using experimental and computational approaches. As part of computational approaches, human head finite element (FE) models show to be important tools in the analysis of TBIs, making it possible to estimate local mechanical effects on brain tissue for different accident scenarios. The present study aims to contribute to the computational approach by means of the development of three advanced FE head models for accurately describing the head tissue dynamics, the first step to predict TBIs.

METHODS

We have developed three detailed FE models of human heads from magnetic resonance images of three volunteers: an adult female (32 yrs), an adult male (35 yrs), and a young male (16 yrs). These models have been validated against experimental data of post mortem human subjects (PMHS) tests available in the literature. Brain tissue displacements relative to the skull, hydrostatic intracranial pressure, and head acceleration have been used as the parameters to compare the model response with the experimental response for validation. The software CORAplus (CORrelation and Analysis) has been adopted to evaluate the bio-fidelity level of FE models.

RESULTS

Numerical results from the three models agree with experimental data. FE models presented in this study show a good bio-fidelity for hydrostatic pressure (CORA score of 0.776) and a fair bio-fidelity brain tissue displacements relative to the skull (CORA score of 0.443 and 0.535). The comparison among numerical simulations carried out with the three models shows negligible differences in the mechanical state of brain tissue due to the different morphometry of the heads, when the same acceleration history is considered.

CONCLUSIONS

The three FE models, thanks to their accurate description of anatomical morphology and to their bio-fidelity, can be useful tools to investigate brain mechanics due to different impact scenarios. Therefore, they can be used for different purposes, such as the investigation of the correlation between head acceleration and tissue damage, or the effectiveness of helmet designs. This work does not address the issue to define injury thresholds for the proposed models.

Improving Spatial Hearing when Wearing Ski Helmets in Order to Increase Safety on Ski Slopes

This study investigated the effect of a new type of ear pads for ski helmets on the hearing performance of 13 young adults (mean age: 22 years). Free-field hearing thresholds and sound localization performance of the subjects were assessed in three conditions: without helmet, with a conventional helmet and with the modified helmet. Results showed that the modified helmet was superior to the conventional helmet in all respects, but did not allow for a performance level observed without a helmet. Considering the importance of precise hearing and sound localization during alpine skiing, acoustically improved ear pads of ski helmets, as demonstrated in this study, can essentially contribute to enhancing the safety on ski slopes.

Maxillofacial Injuries Sustained by Riders of Electric-Powered Bikes and Electric-Powered Scooters

OBJECTIVES

The purpose of our study is to retrospectively analyze and compare the patterns of maxillofacial-related injuries among rides of electric-powered bikes (E-bikes) and electric-powered scooters (E-scooters), the associated risk factors, and the required treatment.

MATERIALS AND METHODS

The medical files of all riders presenting to the emergency department at the Tel Aviv Sourasky Medical Center between 2019 and 2020 with oral- and maxillofacial-related injuries due to E-bike and E-scooter accidents were reviewed.

RESULTS

A total of 320 riders sustained oral- and maxillofacial-related injuries due to trauma involving E-bikes and E-scooters during the study period. E-scooter riders were involved in 238 accidents (74.5%) while E-bike riders accounted for the remaining 82 accidents (27.5%). Eighty-four out of 320 riders (26.25%) were hospitalized and required surgical interventions. Most of the 232 riders (72.5%) who reported not wearing a protective helmet during the index accident were E-scooter riders. In addition, 39 riders (18.66%) were riding either of these electric-powered vehicles under the influence of alcohol.

CONCLUSIONS

E-bike riders are more likely to sustain a maxillofacial fracture than E-scooter riders. Not wearing a protective helmet and riding under the influence of alcohol are major risk factors for maxillofacial injuries.

Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review

BACKGROUND

As a form of the Internet of Things (IoT)-gateways, a smart helmet is one of the core devices that offers distinct functionalities. The development of smart helmets connected to IoT infrastructure helps promote connected health and safety in various fields. In this regard, we present a comprehensive analysis of smart helmet technology and its main characteristics and applications for health and safety.

OBJECTIVE

This paper reviews the trends in smart helmet technology and provides an overview of the current and future potential deployments of such technology, the development of smart helmets for continuous monitoring of the health status of users, and the surrounding environmental conditions. The research questions were as follows: What are the main purposes and domains of smart helmets for health and safety? How have researchers realized key features and with what types of sensors?

METHODS

We selected studies cited in electronic databases such as Google Scholar, Web of Science, ScienceDirect, and EBSCO on smart helmets through a keyword search from January 2010 to December 2021. In total, 1268 papers were identified (Web of Science: 87/1268, 6.86%; EBSCO: 149/1268, 11.75%; ScienceDirect: 248/1268, 19.55%; and Google Scholar: 784/1268, 61.82%), and the number of final studies included after PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) study selection was 57. We also performed a self-assessment of the reviewed articles to determine the quality of the paper. The scoring was based on five criteria: test environment, prototype quality, feasibility test, sensor calibration, and versatility.

RESULTS

Smart helmet research has been considered in industry, sports, first responder, and health tracking scenarios for health and safety purposes. Among 57 studies, most studies with prototype development were industrial applications (18/57, 32%), and the 2 most frequent studies including simulation were industry (23/57, 40%) and sports (23/57, 40%) applications. From our assessment-scoring result, studies tended to focus on sensor calibration results (2.3 out of 3), while the lowest part was a feasibility test (1.6 out of 3). Further classification of the purpose of smart helmets yielded 4 major categories, including activity, physiological and environmental (hazard) risk sensing, as well as risk event alerting.

CONCLUSIONS

A summary of existing smart helmet systems is presented with a review of the sensor features used in the prototyping demonstrations. Overall, we aimed to explore new possibilities by examining the latest research, sensor technologies, and application platform perspectives for smart helmets as promising wearable devices. The barriers to users, challenges in the development of smart helmets, and future opportunities for health and safety applications are also discussed. In conclusion, this paper presents the current status of smart helmet technology, main issues, and prospects for future smart helmet with the objective of making the smart helmet concept a reality.

[Endoscopy-Assisted Suturectomy and Cranial Remodeling Orthosis for Craniosynostosis]

Craniosynostosis(CS)is now being diagnosed early as Japanese parents have become more conscious of the infants' skull shape. Endoscopy-assisted suturectomy(EAS)is a surgical treatment for early infants in combination with postoperative helmet cranial remodeling. Here we report our operative experiences with EAS for the treatment of CS. EAS is minimally invasive and has yielded good results when performed in combination with helmet therapy. However, transfusion for almost half of patients and additional surgery for syndromic patients were required. We will further develop the bone resection technique and hemostasis methods.

Characterizing Exposure to Head Acceleration Events in Youth Football Using an Instrumented Mouthpiece

Understanding characteristics of head acceleration events (HAEs) in youth football is vital in developing strategies to improve athlete safety. This study aimed to characterize HAEs in youth football using an instrumented mouthpiece. Youth football athletes (ages 11-13) participating on two teams were enrolled in this study for one season. Each athlete was instrumented with a mouthpiece-based sensor throughout the season. HAEs were verified on film to ensure that mouthpiece-based sensors triggered during contact. The number of HAEs, peak resultant linear and rotational accelerations, and peak resultant rotational velocity were quantified. Mixed effects models were used to evaluate differences in mean kinematic metrics among all HAEs for session type, athlete position, and contact surface. A total of 5,292 HAEs were collected and evaluated from 30 athletes. The median (95th percentile) peak resultant linear acceleration, rotational acceleration, and rotational velocity was 9.5 g (27.0 g), 666.4 rad s-2 (1863.3 rad s-2), and 8.5 rad s-1 (17.4 rad s-1), respectively. Athletes experienced six (22) HAEs per athlete per session (i.e., practice, game). Competition had a significantly higher mean number of HAEs per athlete per session and mean peak rotational acceleration. Peak resultant rotational kinematics varied significantly among athlete positions. Direct head impacts had higher mean kinematics compared to indirect HAEs, from body collisions. The results of this study demonstrate that session type, athlete position, and contact surface (i.e., direct, indirect) may influence HAE exposure in youth football.

Application of subject-specific helmets for the study of human visuomotor behavior using transcranial focused ultrasound: a pilot study

BACKGROUND AND OBJECTIVE

As a novel non-invasive human brain stimulation method, transcranial focused ultrasound (tFUS) is receiving growing attention due to its superior spatial specificity and depth penetrability. Since the focal point of tFUS needs to be fixated precisely to the target brain region during stimulation, a critical issue is to identify and maintain the accurate position and orientation of the tFUS transducer relative to the subject's head. This study aims to propose the entire framework of tFUS stimulation integrating the methods previously proposed by the authors for tFUS transducer configuration optimization and a subject-specific 3D-printed helmet, and to validate this complete setup in a human behavioral neuromodulation study.

METHODS

To find the optimal configuration of the tFUS transducer, a numerical method based on subject-specific tFUS beamlines simulation was used. Then, the subject-specific 3D-printed helmet has been applied to effectively secure the transducer at the estimated optimal configuration. To validate this tFUS framework, a common behavioral neuromodulation paradigm was chosen; the effect of the dorsolateral prefrontal cortex (DLPFC) stimulation on anti-saccade (AS) behavior. While human participants (n=2) were performing AS tasks, tFUS stimulations were randomly applied to the left DLPFC right after the fixation target disappeared.

RESULTS

The neuromodulation result strongly suggests that the cortical stimulation using the proposed tFUS setup is effective in significantly reducing the error rates of anti-saccades (about -10 %p for S1 and -16 %p for S2), whereas no significant effect was observed on their latencies. These observed behavioral effects are consistent with the previous results based on conventional brain stimulation or lesion studies.

CONCLUSIONS

The proposed subject-specific tFUS framework has been effectively used in human neuromodulation study. The result suggests that the tFUS stimulation targeted to the DLPFC can generate a neuromodulatory effect on AS behavior.

Traumatic Brain Injury in Underage Motorcycle Drivers: Clinical Outcomes and Sociocultural Attitudes from a Lower-Middle-Income Country

BACKGROUND AND OBJECTIVE

Poor societal attitudes and inadequate law enforcement have greatly contributed to the increase in underage motorcycle driving in Pakistan. This study reports the burden of traumatic brain injury (TBI), clinical characteristics/outcomes, and reason for driving in underage motorcyclists.

MATERIALS AND METHODS

A prospective study was conducted throughout 2021. Demographics, mechanism of injury, helmet use, number of passengers, clinical outcomes, reason for driving and parental awareness/consent status, referral pathway, and transport duration were documented.

RESULTS

Of a total of 1052 motorcyclists with TBI, 112 were underage drivers. The mean age was 14.7 years (range, 10-17 years); 98.2% were male and 17% wore protective helmets. The most common reason for driving was recreational, followed by for domestic chores. In 66 patients, there was parental awareness and 30 of these patients had active parental consent. These patients reported domestic chores as the reason for their journey, whereas recreational purposes were a more prevalent reason in patients without parental awareness/consent (P < 0.001). Most patients were brought by provincial ambulance service (response time 12.8 minutes). Some patients came from peripheral hospitals (26.8%) and private hospitals (14.3%) that lacked neurosurgical cover, and these were associated with severer baseline injuries (P < 0.001). The average stay was 6.5 days, and 75.9% of patients were discharged with a good Glasgow Outcome Scale score.

CONCLUSIONS

Most underage patients with TBI resulting from motorcycle driving are adolescent boys who do not use helmets. Trauma prevention systems and involvement of multiple stakeholders are needed to reduce underage driving. Efficient referral systems must transport patients to appropriate neurosurgical cover, which is lacking outside major cities.

Hypopharynx, oropharynx morphology and histology in severe Coronavirus 2 patients treated by noninvasive ventilation: comparison between full-face mask and helmet strategies

BACKGROUND

Non-invasive ventilation may alter the morphology and histology of the upper airway mucosa. This study aimed to investigate the alterations of hypopharynx and oropharynx mucosa, identified during oro-tracheal intubation procedure via video-assisted laryngoscopy, in severe acute respiratory syndrome Coronavirus 2 related, treated by non-invasive ventilation via full-face mask or helmet.

METHODS

Data of patients affected by Coronavirus 2 admitted to COVID Hospital of L'Aquila (Italy), presenting hypopharynx and oropharynx morphology alterations, requiring oro-tracheal intubation for invasive ventilation and initially treated with non-invasive ventilation were included in the study. The study aimed to investigate the upper airway mucosa alterations using oropharyngeal and hypopharyngeal images and biopsies taken during video-assisted-laryngoscopy. Data from the hypopharynx and oropharynx morphology and histology alterations between non-invasive ventilation via a full-face mask or helmet used during hospitalization were compared.

RESULTS

From 220 data recorded, 60 patients were included in the study and classified into non-invasive ventilation full-face mask group (30/60) and via helmet group. Comparing data between groups, significant differences were found with respect to hyperemia (77% vs. 20%), laryngeal bleeding ulcerations (87% vs. 13%), and vocal cord edema with >50% narrowing of the tracheal lumen (73% vs. 7%), respectively. The histology examination revealed fibrin-necrotic exudate with extensive necrotic degenerative changes in the sample tissue of the groups. There were not any differences in the duration time of non-invasive ventilation, time from hospitalization and the start of ventilation between groups.

CONCLUSIONS

The data from this research suggested that there were differences in airway mucosa damages among patients treated with a full-face mask or helmet. Further studies should be planned to understand which non-invasive ventilation support may mitigate upper airway mucosa damages when oro-tracheal intubation is requested for invasive respiratory support.

[Traumatic brain injuries in winter sports : An overview based on the winter sports skiing, snowboarding and ice hockey]

In winter sports, skiers, snowboarders and ice hockey players have the highest risk of traumatic brain injuries (TBI). In skiing/snowboarding severe TBIs are of concern; in ice hockey, repetitive minor TBIs are frequent. The main causes of TBI in recreational skiing are collisions with trees; in professionals falls due to technical or tactical mistakes are the main causes. In ice hockey 10-15% of all injuries are due to a sports-related concussion (SRC), mostly caused by player-opponent contact. The pathomechanism in TBI is a combination of rotational and linear acceleration during head impact, which causes a diffuse axonal injury. Long-term complications such as neurodegenerative diseases and functional deficits are of relevance. Prevention by wearing helmets is effective, but less effective in TBI/SRC than in focal injuries.

Collegiate athletes opinions regarding helmet use while riding scooters or mopeds

Many collegiate athletes use scooters and mopeds for transportation, and they are at greater risk for head injury without helmets. Objective: Investigate college athletes' reasons for wearing/not wearing helmets while riding a scooter or moped. Participants, Methods: 125 Division I athletes across five teams (two with helmet mandates) completed a cross sectional survey on rates and attitudes about helmet use on scooters or mopeds. Results: Helmet use on mandated vs non-mandated teams was 100% vs 3.6% (OR 1141; 95% CI 56.97, 22,850). For the question, "if you do not wear a helmet, what might make you change your mind and wear one?", players most commonly wrote in a law or coaches' rule (57%). Conclusions: A coach's rule is associated with a higher rate of helmet use in collegiate athletes, and athletes primarily report a rule or law as the reason they would wear a helmet on a scooter or moped.

Exploration of motorcyclists' red-light running and helmet use at signalized intersections in Ghana

OBJECTIVE

There is a dearth of empirical studies on motorcyclists' red-light running and helmet use at signalized intersections in low and middle-income countries like Ghana, Nigeria and Malaysia. This study seeks to fill the gap by looking at red-light running and helmet use at signalized intersections in the Cape Coast metropolis, Ghana. The study also identified potential areas of intervention to reduce the dangers posed by motorcyclists' red-light running in the Cape Coast Metropolis without the use of a helmet.

METHOD

A naturalistic exploratory un-obstructive observational approach was used in assessing this phenomenon. The relationship between motorcyclists' behaviors and motorcyclists' observed demographic characteristics, the locality of the intersection, time of the week and presence of pillion passengers were analyzed. Chi-Square test of independence was used to establish the statistically significant relationships between dependent and independent variables.

RESULTS

In all, 2,225 motorcyclists and 744 pillion passengers were observed. The results revealed that 33.1% of the motorcyclists ran a red light with 45.4% not using a helmet. Red-light running at signalized intersections was significantly linked to the locality of the intersection, time of the week, and helmet use. The helmet use was low and significantly associated with the presence of a pillion passenger and whether the pillion passenger used a helmet or not.

CONCLUSION

Red-light running is influenced by locality of intersection, time of the week and helmet use. Efforts to reduce red-light running and improve helmet use should involve road safety education, awareness creation, and enforcement of traffic laws by the officials of the National Road Safety Authority and Motor Transport and Traffic Department of the Ghana Police Service. City managers in other low and middle-income countries can use the findings in the study to inform policy.

Workshop Safety Helmet Wearing Detection Model Based on SCM-YOLO

In order to overcome the problems of object detection in complex scenes based on the YOLOv4-tiny algorithm, such as insufficient feature extraction, low accuracy, and low recall rate, an improved YOLOv4-tiny safety helmet-wearing detection algorithm SCM-YOLO is proposed. Firstly, the Spatial Pyramid Pooling (SPP) structure is added after the backbone network of the YOLOv4-tiny model to improve its adaptability of different scale features and increase its effective features extraction capability. Secondly, Convolutional Block Attention Module (CBAM), Mish activation function, K-Means++ clustering algorithm, label smoothing, and Mosaic data enhancement are introduced to improve the detection accuracy of small objects while ensuring the detection speed. After a large number of experiments, the proposed SCM-YOLO algorithm achieves a mAP of 93.19%, which is 4.76% higher than the YOLOv4-tiny algorithm. Its inference speed reaches 22.9FPS (GeForce GTX 1050Ti), which meets the needs of the real-time and accurate detection of safety helmets in complex scenes.

Non-motorised active mobility device use by children in Singapore: Injury patterns and risk factors for severe injury

INTRODUCTION

Wheeled recreational devices (WRDs) include tricycles, bicycles, scooters, inline skates, skateboards, longboards and waveboards, and can cause significant morbidity and mortality. This study aimed to describe the epidemiology and nature of injuries sustained by children from WRD use, and risk factors for severe injury.

METHOD

We described injuries relating to WRD use in children <18 years who presented to the emergency department of an Asian tertiary hospital between 2016 and 2020. Demographic data, site and nature of the injury, and historical trends were analysed. Risk factors for severe injury (defined as fractures or dislocations), Injury Severity Score ≥9, and injuries resulting in hospitalisation, surgery or death were evaluated.

RESULTS

A total of 5,002 patients with 5,507 WRD-related injuries were attended to over the 5-year study period. Median age was 4.7 years. Injuries related to bicycles (54.6%) and scooters (30.3%) were most frequent, followed by skateboards and waveboards (7.4%), inline skates (4.7%), and tricycles (3.0%). Injuries occurred most frequently in public spaces. Soft tissue injuries (49.3%) and fractures (18.7%) were the most common diagnoses. Upper limb (36.4%) and head and neck (29.0%) regions were the most common sites of injury. Among the patients, 1,910 (38%) had severe injuries with potential morbidity. On multivariate analysis, heavier children of the school-going age who use either scooters, skateboards or inline skates are more prone to severe injuries. Involvement in a vehicular collision was a negative predictor.

CONCLUSION

WRD use in children can result in severe injuries. Wrist and elbow guards, as well as helmets are recommended, along with adequate parental supervision.

The Influence of Protective Headgear on the Visual Field of Recreational-Level Skiers

The benefit of protective headgear for recreational skiers is an ongoing debate in the snow sports industry, and there are a lot of opposing opinions. Due to the dynamic conditions in which winter sports are performed, athletes demand rapid and constant processing of visual information. A sufficient level of anticipation helps athletes to properly position themselves to reduce the forces transferred to the head or even move to avoid a collision. To objectively identify the impact of protective headgear on the visual field when skiing, it is necessary to conduct suitable measurements. The sample consisted of 43 recreational-level skiers (27 M, 16 F; age 31.6 ± 8.23 years). A predefined testing protocol on an ortoreter was used to assess the visual field for three conditions of wearing protective headgear. Differences in perceived visual stimuli between the three conditions were evaluated by repeated measures analysis of variance (ANOVA). Based on the observed results, it can be concluded that the combination of wearing a ski helmet and ski goggles significantly negatively influences visual performance in a way that the visual field is narrowed, for both helmet users and non-users, only when comparing the tested conditions. When comparing helmet users and non-users, there are no differences in the amount of visual impairment; therefore, the habit of wearing a helmet does not influence the ability of perceiving visual stimuli.

Temporal Instability of Factors Affecting Injury Severity in Helmet-Wearing and Non-Helmet-Wearing Motorcycle Crashes: A Random Parameter Approach with Heterogeneity in Means and Variances

Not wearing a helmet, not properly strapping the helmet on, or wearing a substandard helmet increases the risk of fatalities and injuries in motorcycle crashes. This research examines the differences in motorcycle crash injury severity considering crashes involving the compliance with and defiance of helmet use by motorcycle riders and highlights the temporal variation in their impact. Three-year (2017-2019) motorcycle crash data were collected from RESCUE 1122, a provincial emergency response service for Rawalpindi, Pakistan. The available crash data include crash-specific information, vehicle, driver, spatial and temporal characteristics, roadway features, and traffic volume, which influence the motorcyclist's injury severity. A random parameters logit model with heterogeneity in means and variances was evaluated to predict critical contributory factors in helmet-wearing and non-helmet-wearing motorcyclist crashes. Model estimates suggest significant variations in the impact of explanatory variables on motorcyclists' injury severity in the case of compliance with and defiance of helmet use. For helmet-wearing motorcyclists, key factors significantly associated with increasingly severe injury and fatal injuries include young riders (below 20 years of age), female pillion riders, collisions with another motorcycle, large trucks, passenger car, drivers aged 50 years and above, and drivers being distracted while driving. In contrast, for non-helmet-wearing motorcyclists, the significant factors responsible for severe injuries and fatalities were distracted driving, the collision of two motorcycles, crashes at U-turns, weekday crashes, and drivers above 50 years of age. The impact of parameters that predict motorcyclist injury severity was found to vary dramatically over time, exhibiting statistically significant temporal instability. The results of this study can serve as potential motorcycle safety guidelines for all relevant stakeholders to improve the state of motorcycle safety in the country.

Association Between Head Impact Biomechanics and Physical Load in College Football

Head impacts and physical exertion are ubiquitous in American football, but the relationship between these factors is poorly understood across a competitive season or even within an individual session. Gameplay characteristics, including player position and session type, may contribute to these relationships but have not been prospectively examined. The current study aimed to determine if an association exists between head impact biomechanics and physical load metrics. We prospectively studied college football players during the 2017–2021 football seasons across representative playing positions (15 offensive and defensive linemen, 11 linebackers and tight ends, and 15 defensive backs, running backs, and receivers). Participants wore halters embedded with Catapult Vector GPS monitoring systems to quantify player load and participant helmets were equipped with the Head Impact Telemetry System to quantify head impact biomechanics and repetitive head impact exposure (RHIE). Generalized linear models and linear regression models were employed to analyze in-session and season-long outcomes, while addressing factors such as player position and session type on our data. Player load was associated with RHIE (p < 0.001). Season-long player load predicted season-long RHIE (R² = 0.31; p < 0.001). Position group affected in-session player load (p = 0.025). Both player load and RHIE were greater in games than in practices (p < 0.001), and position group did not affect RHIE (p = 0.343). Physical load burden was associated with RHIE within sessions and across an entire season. Session type affected both RHIE and player load, while position group only affected player load. Our data point to tracking physical load burden as a potential proxy for monitoring anticipated RHIE during the season.

Characteristics and Risk Factors for Electric Scooter-Related Crashes and Injury Crashes among Scooter Riders: A Two-Phase Survey Study

Electric scooters (or e-scooters) are among the most popular micromobility options that have experienced an enormous expansion in urban transportation systems across the world in recent years. Along with the increased usage of e-scooters, the increasing number of e-scooter-related injuries has also become an emerging global public health concern. However, little is known regarding the risk factors for e-scooter-related crashes and injury crashes. This study consisted of a two-phase survey questionnaire administered to a cohort of e-scooter riders (n = 210), which obtained exposure information on riders' demographics, riding behaviors (including infrastructure selection), helmet use, and other crash-related factors. The risk ratios of riders' self-reported involvement in an e-scooter-related crash (i.e., any crash versus no crash) and injury crash (i.e., injury crash versus non-injury crash) were estimated across exposure subcategories using the Negative Binomial regression approach. Males and frequent users of e-scooters were associated with an increased risk of e-scooter-related crashes of any type. For the e-scooter-related injury crashes, more frequently riding on bike lanes (i.e., greater than 25% of the time), either protected or unprotected, was identified as a protective factor. E-scooter-related injury crashes were more likely to occur among females, who reported riding on sidewalks and non-paved surfaces more frequently. The study may help inform public policy regarding e-scooter legislation and prioritize efforts to establish suitable road infrastructure for improved e-scooter riding safety.

Multi-Scale Safety Helmet Detection Based on RSSE-YOLOv3

Due to the shielding of dense and small targets, real-time detection of whether construction workers are wearing safety helmets suffers from low detection accuracy and missed detection. In this paper, a new detection algorithm based on YOLOv3 is proposed. Firstly, the parallel network RepVGG Skip Squeeze Excitation (RSSE) module is used to replace the Res8 module in the original YOLOv3 network. The RSSE module consists of 3 × 3 convolutional fusion channels and SSE branches fused. The introduction of the R-SSE module increases the network width, reduces the network depth, and improves the network detection speed and accuracy. Secondly, to avoid gradient disappearance and improve feature reuse, the residual module Res2 is used to replace the CBL×5 modules. Finally, the resolution of the input image is improved, and the four-scale feature prediction is used instead of the three-scale feature prediction to further improve the efficiency of detecting small targets. This paper also introduces the complete joint crossover (CIOU) to improve the loss function and positioning accuracy. The experimental results show that, compared with the original YOLOv3 algorithm, the improved algorithm improves the precision (P) by 3.9%, the recall (R) by 5.2%, and the average precision (mAP) by 4.7%, which significantly improves the performance of the detection.

Is the Use of Segways or E-Scooters in Urban Areas a Potential Health Risk? A Comparison of Trauma Consequences

Background and objectives: Electromobility has become increasingly popular. In 2001, Segway personal transporters (Segway) were established for tourists, and e-scooters have been in use since their approval in 2019. The aim of this study was to analyze and compare the types of injuries directly related to the use of Segways and e-scooters, respectively, in a German city and to phrase potential safety advice. Materials and Methods: All patients presenting to our emergency department after Segway incidents were retrospectively analyzed and compared with the prospectively collected cohort of patients following e-scooter incidents. Presented injuries were analyzed by body region and injury severity score (ISS). Epidemiological data were collected. Results: Overall, 171 patients were enrolled. The Segway group included 56 patients (mean age 48 years), and the e-scooter group consisted of 115 patients (mean age 33.9 years). Head injuries (HI) occurred in 34% in the Segway group compared to 52% in the e-scooter group. The ISS was approximately equal for both groups (mean ISS Segway group: 6.9/e-scooter group: 5.6). Conclusions: Since the e-scooter group presented a high number of HI along with a higher likelihood and greater severity of HI, mandatory use of helmets is suggested.

Characteristics of Electric Scooter and Bicycle Injuries After Introduction of Electric Scooter Rentals in Oslo, Norway

IMPORTANCE

When society introduces and accepts new transportation modes, it is important to map risks and benefits.

OBJECTIVE

To compare electric scooter (e-scooter) and bicycle injuries.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study is based on prospectively collected data on Norwegian patients who sustained e-scooter or bicycle injuries and presented to an emergency department affiliated with Oslo University Hospital between January 1, 2019, and March 31, 2020.

MAIN OUTCOMES AND MEASURES

e-Scooter and bicycle injuries were evaluated for associations with sex, age, time of injury, helmet use, intoxication, body region, and injury severity. Descriptive statistics are presented as mean (SD) or number with percentage, with significance set at P < .05 (2-tailed).

RESULTS

During the study period, 3191 patients were included (850 e-scooter riders, 2341 bicyclists) with 3839 injuries recorded (997 e-scooter, 2842 bicycle). The mean (SD) age of those injured was 34 (17) years, 2026 riders (63.5%) were male, 1474 (46.2%) were helmeted at the time of injury, and 516 (16.2%) were intoxicated by alcohol or other drugs. The annual incidence of injuries was 120 per 100 000 inhabitants for e-scooters and 340 per 100 000 inhabitants for bicycles. Men were overrepresented in both groups (529 e-scooter riders [62.2%] and 1497 bicyclists [63.9%]). e-Scooter riders were younger than bicyclists (mean [SD] age, 31 [12] vs 35 [18] years). Most injured e-scooter riders were aged 20 to 40 years, whereas injured bicyclists had a broader age distribution. e-Scooter injuries commonly occurred on weekends (378 [46.6%]) and during evening (230 [32.3%]) or nighttime (242 [34.1%]) hours. Most bicycle injuries occurred during weekdays (1586 [69.7%]) and daytime (1762 [61.3%]). e-Scooter riders were more often intoxicated (336 [39.5%] vs 180 [7.7%]) and had a lower rate of helmet use (18 [2.1%] vs 1456 [62.2%]). During nighttime, 230 injured e-scooter riders (91.3%) and 86 bicyclists (69.4%) were intoxicated. e-Scooter riders had more head and neck (317 [31.7%] vs 636 [22.4%]) and lower-limb (285 [28.6%] vs 632 [22.2%]) injuries and fewer upper-limb (341 [34.2%] vs 1276 [44.9%]), thoracic (41 [4.1%] vs 195 [6.9%]), and abdominal, pelvic, and lumbar (13 [1.3%] vs 103 [3.6%]) injuries.

CONCLUSIONS AND RELEVANCE

In this cohort study, e-scooter riders were younger than bicyclists, did not use helmets, were more often intoxicated, and were more often injured during nighttime. The rate of intoxication among e-scooter riders injured at night was high. Preventive measures, including awareness campaigns, regulating e-scooter availability, improving infrastructure, and implementing stricter helmet and alcohol policies, may prove effective for reducing injuries.

Estimation of Head Accelerations in Crashes Using Neural Networks and Sensors Embedded in the Protective Helmet

Traumatic Brain Injuries (TBIs) are one of the most frequent and severe outcomes of a Powered Two-Wheeler (PTW) crash. Early diagnosis and treatment can greatly reduce permanent consequences. Despite the fact that devices to track head kinematics have been developed for sports applications, they all have limitations, which hamper their use in everyday road applications. In this study, a new technical solution based on accelerometers integrated in a motorcycle helmet is presented, and the related methodology to estimate linear and rotational acceleration of the head with deep Artificial Neural Networks (dANNs) is developed. A finite element model of helmet coupled with a Hybrid III head model was used to generate data needed for the neural network training. Input data to the dANN model were time signals of (virtual) accelerometers placed on the inner surface of the helmet shell, while the output data were the components of linear and rotational head accelerations. The network was capable of estimating, with good accuracy, time patterns of the acceleration components in all impact conditions that require medical treatment. The correlation between the reference and estimated values was high for all parameters and for both linear and rotational acceleration, with coefficients of determination (R2) ranging from 0.91 to 0.97.

Saving lives through road safety risk factor interventions: global and national estimates

Global road mortality is a leading cause of death in many low-income and middle-income countries. Data to support priority setting under current resource constraints are urgently needed to achieve Sustainable Development Goal (SDG) 3.6. This Series paper estimates the potential number of lives saved if each country implemented interventions to address risk factors for road injuries. We did a systematic review of all available evidence-based, preventive interventions for mortality reduction that targeted the four main risk factors for road injuries (ie, speeding, drink driving, helmet use, and use of seatbelt or child restraint). We used literature review variables and considered three key country-level variables (gross domestic product per capita, population density, and government effectiveness) to generate country-specific estimates on the potential annual attributable number of lives that would be saved by interventions focusing on these four risk factors in 185 countries. Our results suggest that the implementation of evidence-based road safety interventions that target the four main road safety risk factors could prevent between 25% and 40% of all fatal road injuries worldwide. Interventions addressing speed could save about 347 258 lives globally per year, and at least 16 304 lives would be saved through drink driving interventions. The implementation of seatbelt interventions could save about 121 083 lives, and 51 698 lives could be saved by helmet interventions. We identify country-specific estimates of the potential number of lives saved that would be attributable to these interventions. Our results show the potential effectiveness of the implementation and scaling of these interventions. This paper presents key evidence for priority setting on road safety interventions and shows a path for reaching SDG 3.6.

Investigating the Difference in Factors Contributing to the Likelihood of Motorcyclist Fatalities in Single Motorcycle and Multiple Vehicle Crashes

In order to better understand the factors affecting the likelihood of motorcyclists' fatal injuries, motorcycle-involved crashes were investigated based on the involvement of the following vehicles: single motorcycle (SM), multiple motorcycles (MM) and motorcycle versus vehicle (MV) crashes.

METHOD

Binary logit and mixed logit models that consider the heterogeneity of parameters were applied to identify the critical factors that increase the likelihood of motorcyclist fatality.

RESULTS

Mixed logit models were found to have better fitting performances. Factors that increase the likelihood of motorcyclist fatality include lanes separated by traffic islands, male motorcyclists, and riding with BAC values of less than the legally limited value. Collisions with trees or utility poles lead to the highest likelihood of fatality in SM crashes. The effects of curved roads, same-direction swipe crashes, youth, and unlicensed motorcyclists are only significant in the likelihood of fatality in SM crashes.

CONCLUSIONS

Motorcyclists tend to be killed if they collide with large engine-size motorcycles and vehicles, unlicensed motorcyclists, or drivers with speeding related or right-of-way violations with positive BAC values. Driving or riding should be prohibited for any amount of alcohol or for anyone with a positive BAC value. Law enforcement should focus on unlicensed, speeding motorcyclists and drivers, and those who violate the right of way or perform improper turns. Roadside objects and facilities should be checked for appropriate placement and be equipped with reflective devices or injury protection facilities.

Sensitivity Analysis of Circular and Helmet Coil Arrays in Magnetic Induction Tomography for Stroke Detection

Magnetic induction tomography (MIT) is harmless and contactless technique for measuring the conductivity of the biological tissue. MIT could be used for initial diagnosis and continuous monitoring of stroke. Different kinds of coil arrays have been proposed for MIT systems. Previous research results using a circular 16-channel MIT model reported difficulties with detection and measurement of small bioelectric signals. For stroke imaging, a system with a higher sensitivity is required. We aim to improve the sensitivity by increasing the number of coils and placing them closer to the head. In this paper, a helmet type coil array with 31 coils is introduced. For simplicity, the head is modelled as a sphere with white matter as a material. The stroke is simulated as a single inclusion with blood and assigned different sizes and positions. Sensitivity distribution and target response of the stroke were evaluated for the helmet model and compared with the circular MIT system. The simulations and analysis were performed at 10 MHz frequency with different coil pairs. Results from comparison of the two MIT models show that the Helmet coil array provides better spatial sensitivity, which has been estimated to be more than 20 times higher than the circular model. Further, when all coils are taken in account, the recorded sensitivity improvement was in the range of 13-90-fold.

Reducing the neurotrauma burden in India- a national mobilization

India has one of the highest TBI burdens due to RTA, with 60% of head injuries being attributable to RTA and more than 150000 lives being lost annually due to TBI. These numbers have prompted institutions and organizations at international, national and local levels to mobilize and address this burden through prevention, pre-hospital care and in hospital care. Academic institutions such as the AMC have run local campaigns promoting the wearing of helmets when riding two-wheelers. Prehospital care institutions such as GVK-EMRI have also made large strides nationally on delivering safe and timely care through novel and focused education to its EMTs, applying evidence-based practice to all facets of its work. These led to implementation of novel and innovative technological solutions faster and more efficient responses. National institutions such as the NSI and NTSI have been instrumental in promoting safety measures such as helmets and use of seat belts through social media videos, often using celebrities to disseminate the message. NSI have also focused on sharing best practices for the management of TBI through easy-to-use platforms such as YouTube. Institutions such as AAPI, NSI and NTSI have collaboratively developed TBI management guidelines that are specific to the Indian population (supported by AASAN). NGOs such as the IHIF and SLF have contributed to this movement by promoting awareness through campaigns and public education. While TBI remains a large burden in India, a mobilization, and coalesced efforts of such a scale holds promise tackling this burden.

Pediatric electric scooter injuries in the UK: Case series and review of literature

OBJECTIVE

Electric scooters are being used worldwide as a new means of transport and e-scooter shared schemes are currently being piloted in cities across the UK. At present, there is no data published looking at pediatric e-scooter injuries within the UK. We aim to assess if e-scooters pose a risk to children and the patterns and severity of orthopedic injuries related to their use.

METHODS

We performed a retrospective review of all orthopedic pediatric referrals relating to e-scooter use from January 1 to December 31, 2020 at two hospitals, including one pediatric Major Trauma Center in central London. Data including patient demographics, mechanism of injury, diagnosis, and treatment were collected.

RESULTS

Ten patients were identified in this series, of which 5 required orthopedic surgery. Four patients required admission to hospital from the emergency department. The median age was 15 (range 13-17 years) and all were male. All e-scooters were privately owned and all sustained a fall whilst riding the e-scooter. No patient was wearing a helmet. Six sustained lower limb injuries and four upper limb injuries. Two patients were trauma called and one patient sustained an open fracture. There were no mortalities at 30 days.

CONCLUSION

E-scooters pose a significant risk to children and can be associated with severe musculoskeletal injury. The risk they pose to the pediatric population should not be overlooked and these findings may inform public policy regarding the restriction of electric scooter use in children.

Electric Scooter-Related Trauma in Korea

BACKGROUND

The number of users of electric scooters, which provide swift and convenient mobility options, has increased sharply over recent years as their distribution as a shared service has expanded. Although the number of accidents and related damage has increased accordingly, limited research has analyzed data on the new types of accidents arising from electric scooters. This study aimed to analyze data on trauma characteristics due to accidents that occurred during electric scooter use.

METHODS

A retrospective chart review was conducted for patients who visited the regional trauma center of our institute due to electric scooter accidents from April 2018 to October 2021. Information was extracted on helmet-wearing status, sex, age, drinking status, accident timeframe, accident mechanism, electric scooter proficiency (period of use), injury severity, severe trauma, lethality, admission to the intensive care unit, surgery under general anesthesia, and the trauma region.

RESULTS

Among the 108 patients involved in electric scooter accidents, 92 patients were not wearing a helmet. Eighty-nine patients (85.2%) were male. The average age of the patients without a helmet was 31.3 years, while that of patients with a helmet was 34.1 years. The most frequent causes of accidents were lack of electric scooter operation experience and falling off the scooter due to obstacles (90 cases). Whether surgery was performed under general anesthesia was not associated with helmet use or non-use, although all patients who underwent facial fracture surgery were not wearing a helmet.

CONCLUSION

The craniofacial region was most frequently affected in electric scooter accidents and wearing a helmet was the best way to prevent craniofacial trauma. Although helmet-wearing is mandatory, the majority of treated patients were not wearing a helmet at the time of injury. Thus, there is an urgent need to introduce a helmet rental system, as well as strict legal requirements, to improve this situation.

Barriers and factors associated with the use of helmets by Motorcyclists: A scoping review

Road Traffic Injuries (RTIs) have imposed a great global burden on public health. Motorcyclists and pedestrians comprise the most significant proportion of this burden. Several studies have demonstrated a link between helmet wearing and a decline in the impact of RTIs in motorcyclists. In this study, we aimed to review the barriers to helmet utilization by motorcyclists. This scoping review has been conducted in accordance with the guidelines for the systematic review of observational studies and the PRISMA Checklist. The search was conducted by using related keywords in EMBASE, PubMed, Scopus, and Cochrane Library. Four independent reviewers carried out the screening. The main outcomes of interest were barriers to helmet usage among motorcyclists, drawn from the finally included studies. Fifty-three records were selected for data extraction. According to these reports, the barriers and factors associated with helmet usage among motorcyclists were categorized into five entities as: legislations/enforcement strategies, helmet disadvantages (discomfort, visual/auditory blockage, and thermal dysregulation), risky behaviors (riding while drunk or high on drugs), sex and/or age factors, and the location and time of the injury event (rural vs. urban locations, day vs. night riding). From the perspective of policymakers, the findings of this review are of utmost importance and could be used in addressing the challenge of inadequate compliance with helmet use.

Surgical helmets can be converted into efficient disinfectable powered air-purifying respirators

BACKGROUND

Filtering facepiece respirators often fail to provide sufficient protection due to a poor fit. Powered air-purifying respirators (PAPRs) are not designed for healthcare personnel, and are challenging to disinfect. Surgical helmets (SH) are available in many United States hospitals but do not provide respiratory protection. Several modifications to SH have been suggested, but none are sufficiently compliant with safety and efficiency standards. The purpose of this investigation was the development of a filter adaptor, which converts SHs into efficient, safe, and disinfectable PAPRs.

METHODS

Four critical features were investigated close to regulatory requirements: total inward leakage of particles, CO₂ concentrations, intra-helmet differential pressure, and automated disinfection.

RESULTS

The average total inward leakage in the 2 independent tests were 0.005% and 0.01%. CO₂ concentrations were lower than in the original SH. The modification generates a positive differential pressure. The filter's performance was not compromised after 50 cycles in a sterilization machine.

DISCUSSION

The modified SH provides several hundred times better protection than FFP-3 masks.

CONCLUSIONS

Surgical helmets can be modified into safe, efficient, and disinfectable PAPRs, suitable for HCP and the operating room in particular. They can play a role in the preparedness for upcoming events requiring efficient respiratory protection.

A data-driven framework for the safe integration of micro-mobility into the transport system: Comparing bicycles and e-scooters in field trials

INTRODUCTION

Recent advances in technology create new opportunities for micro-mobility solutions even as they pose new challenges to transport safety. For instance, in the last few years, e-scooters have become increasingly popular in several cities worldwide; however, in many cases, the municipalities were simply unprepared for the new competition for urban space between traditional road users and e-scooters, so that bans became a necessary, albeit drastic, solution. In many countries, traditional vehicles (such as bicycles) may not be intrinsically safer than e-scooters but are considered less of a safety threat, possibly because-for cyclists-social norms, traffic regulations, and access to infrastructure are established, reducing the number of negative stakeholders. Understanding e-scooter kinematics and e-scooterist behavior may help resolve conflicts among road users, by favoring a data-driven integration of these new e-vehicles into the transport system. In fact, regulations and solutions supported by data are more likely to be acceptable and effective for all stakeholders. As new personal-mobility solutions enter the market, e-scooters may just be the beginning of a micro-mobility revolution.

METHOD

This paper introduces a framework (including planning, execution, analysis, and modeling) for a data-driven evaluation of micro-mobility vehicles. The framework leverages our experience assessing bicycle dynamics in real traffic to make objective and subjective comparisons across different micro-mobility solutions. In this paper, we use the framework to compare bicycles and e-scooters in field tests.

RESULTS

The preliminary results show that e-scooters may be more maneuverable and comfortable than bicycles, although the former require longer braking distances.

PRACTICAL APPLICATIONS

Data collected from e-scooters may, in the short term, facilitate policy making, geo-fencing solutions, and education; in the long run, the same data will promote the integration of e-scooters into a cooperative transport system in which connected automated vehicles share the urban space with micro-mobility vehicles. Finally, the framework and the models presented in this paper may serve as a reference for the future assessment of new micro-mobility vehicles and their users' behavior (although advances in technology and novel micro-mobility solutions will inevitably require some adjustments).

A Comparison of Motorized and Nonmotorized Scooter Injuries in Pediatric Patients Seen in US Emergency Departments

OBJECTIVES

We sought to characterize and compare trends in pediatric injuries sustained on motorized and nonmotorized scooters across the United States, to assess the use of safety equipment in children presenting with scooter-related injuries, and provide strategies for injury prevention.

METHODS

The National Electronic Injury Surveillance System was queried for motorized and nonmotorized scooter-related pediatric injuries from 2014 to 2018 in patients ages 6 to 12 years. Patient demographics, diagnosis, injury location, and narrative of the incident were collected. Bivariate and regression analyses were used to determine demographic and social associations of injury characteristics.

RESULTS

An estimated 146,000 (11,452 motorized and 134,548 nonmotorized) injuries occurred in children ages 6 to 12 years over the 5 years. Three of 4 injuries occurred in children younger than 10 years, and most injuries occurred in males (56%).From 2014 to 2018, the nationwide estimated incidence of motorized scooter injuries increased by 112.1%, while that of nonmotorized scooter injuries decreased by 40.3%.Upper extremity injuries were most common with nonmotorized scooters (44.4% of all injuries), while lower extremity injuries were most common with motorized scooters (39.5% of all injuries). Head and neck injuries accounted for 27.4% of nonmotorized scooter injuries and 23.4% of motorized scooter injuries. The number of concussions in motorized scooters increased from 0.4% in 2014 to 2.7% in 2018, while concussions in nonmotorized scooters decreased from 3.5% to 2.7%. Helmets were mentioned in the medical record in 6.6% of the cases. Of these, 60.5% reported no use of helmet at the time of injury.

CONCLUSIONS

From 2014 to 2018, the number of motorized scooter injuries increased by 112.1% in the pediatric population ages 6 to 12 years, whereas nonmotorized scooter injuries decreased by 40.3%. In more than 60% of the cases that mentioned a helmet, the child injured was recorded as not wearing a helmet. The rise in pediatric injuries associated with motorized scooters in contrast with the reduction of injuries associated with nonmotorized scooters highlights the need for novel public health policies and interventions promoting helmet use with motorized scooters in the pediatric population.

'No-one else wears one:' Exploring farmer attitudes towards All-Terrain Vehicle helmets using the COM-B model

INTRODUCTION

All-Terrain Vehicles (ATV) are a popular piece of farming machinery but are linked to many fatalities and injuries every year. Despite evidence that ATV helmets reduce the risk of serious or fatal injury, research suggests that few farmers wear them. The aim of this study was to explore farmer attitudes toward ATV helmets, using the COM-B model as a framework to identify key barriers and enablers of helmet use and suggest potential interventions to increase helmet use in agriculture.

METHODS

A mixed-methods online survey featuring quantitative and qualitative questions was used to explore key attitudinal factors relevant to farmer helmet wearing. A total of 211 UK and Irish farmers were recruited, including farm owners, managers, workers, and contractors.

RESULTS

Personal exemption from risk, emotional benefits, cognitive barriers, and guideline prompts were all found to be significant predictors of farmer helmet wearing. Key categories within the qualitative data indicated that helmet properties, risk perception, farming culture, and the farming environment could all function as barriers to helmet wearing. Suggested enablers of helmet use included increasing helmet availability and enhancing awareness of the consequences of ATV accidents.

CONCLUSIONS

The key barriers and enablers presented within this paper highlight the relevance of capability (helmet design, time pressure), opportunity (social norms), and motivation (perceived control of risk) when considering farmer helmet wearing behaviors. In order to encourage farmers to wear helmets it will be necessary to design specific interventions using the behavior change wheel.

PRACTICAL APPLICATIONS

Key interventions to prompt helmet use include the inclusion of more cues to prompt helmet wearing (e.g., stickers on the ATV), enhanced training and education, and modelling (e.g., key farming figures shown to wear helmets in the media).

Evaluation of two rotational helmet technologies to decrease peak rotational acceleration in cycling helmets

The risk of brain trauma has been associated with the rotational kinematics leading to the development of helmets with a variety rotational management technologies. The purpose of this paper was to employ a rotation specific test protocol to evaluate the effectiveness of two of these technologies. Dynamic response of the head was measured to assess the performance of each technology. Three cycling helmets with identical construction were included in this study. One helmet with no rotational technology, an established, commercial technology and a novel helmet rotational technology designed and assembled by the authors were tested. A drop test onto a 45° anvil was used to measure the ability of each helmet to manage the dynamic response of the head form during a series of impacts. The results revealed both rotational helmet technologies resulted in lower peak rotational acceleration and brain strain, however each technology demonstrated unique performance characteristics depending on the impact condition.

A Higher Playing Standard, Bowling, and Intermittent Helmet Use Are Related to a Greater Odds of Injury or Concussion in Cricket

OBJECTIVE

To determine if playing position, a higher playing standard, and nonhelmet use are related to an increased odds of joint-specific injury and concussion in cricket.

DESIGN

Cross-sectional cohort.

PARTICIPANTS

Twenty-eight thousand one hundred fifty-two current or former recreational and high-performance cricketers registered on a national database were invited to participate in the Cricket Health and Wellbeing Study. Eligibility requirements were aged ≥18 years and played ≥1 cricket season.

INDEPENDENT VARIABLES

Main playing position (bowler/batter/all-rounder), playing standard (high-performance/recreational), and helmet use (always/most of the time/occasionally/never).

MAIN OUTCOME MEASURES

Cross-sectional questionnaire data included cricket-related injury (hip/groin, knee, ankle, shoulder, hand, back) resulting in ≥4 weeks of reduced exercise and self-reported concussion history. Crude and adjusted (adjusted for seasons played) odds ratios and 95% confidence interval (CIs) were estimated using logistic regression.

RESULTS

Of 2294 participants (59% current cricketers; 97% male; age 52 ± 15 years; played 29 ± 15 seasons; 62% recreational cricketers), 47% reported cricket-related injury and 10% reported concussion. Bowlers had greater odds of hip/groin [odds ratio (95% CI), 1.9 (1.0-3.3)], knee [2.0 (1.4-2.8)], shoulder [2.9 (1.8-4.5)], and back [2.8 (1.7-4.4)] injury compared with batters. High-performance cricketers had greater odds of injury and concussion than recreational cricketers. Wearing a helmet most of the time [2.0 (1.4-3.0)] or occasionally [1.8 (1.3-2.6)] was related to higher odds of self-reported concussion compared with never wearing a helmet. Concussion rates were similar in cricketers who always and never wore a helmet.

CONCLUSIONS

A higher playing standard and bowling (compared with batting) were associated with greater odds of injury. Wearing a helmet occasionally or most of the time was associated with higher odds of self-reported concussion compared with never wearing a helmet.

Posture and Helmet Configuration Effects on Joint Reaction Loads in the Middle Cervical Spine

INTRODUCTION: Between 43 and 97% of helicopter pilots in the Canadian Armed Forces report neck pain. Potential contributing factors include the weight of their helmet, night vision goggles (NVG), and counterweight (CW) combined with deviated neck postures. Therefore, the purpose of this investigation was to quantify changes in neck loads associated with posture, helmet, NVG, and CW.METHODS: Eight male subjects volunteered. They undertook one of five deviated neck postures (flexion, extension, lateral bending, axial rotation) times four configurations (no helmet, helmet only, helmet and NVG, and helmet, NVG, and CW). 3D kinematics and EMG from 10 muscles (5 bilaterally) drove a 3D inverse dynamics, EMG-driven model of the cervical spine which calculated joint compression and shear at C5-C6.RESULTS: The compression in the neutral posture was 116.5 (5.7) N, which increased to 143.7 (11.4) N due to a 12.7 N helmet. NVGs, weighing 7.9 N, also generated this disproportionate increase, where the compression was 164.2 (3.7) N. In flexion or extension, the compression increased with increasing head-supported mass, with a maximum of 315.8 (67.5) N with the CW in flexion. Anteroposterior shear was highest in the lateral bending [34.0 (6.2) N] condition, but was generally low (< 30 N). Mediolateral shear was less than 5 N for all conditions.DISCUSSION: Repositioning the center of gravity of the helmet with either NVGs or CW resulted in posture-specific changes to loading. Posture demonstrated a greater potential to reposition the head segment's center of gravity compared to the helmet design. Therefore, helmet designs which consider repositioning the center of gravity may reduce loads in one posture, but likely exacerbate loading in other postures.Barrett JM, McKinnon CD, Dickerson CR, Laing AC, Callaghan JP. Posture and helmet configuration effects on joint reaction loads in the middle cervical spine. Aerosp Med Hum Perform. 2022; 93(5):458-466.

The Protective Performance of Modern Motorcycle Helmets Under Oblique Impacts

Motorcyclists are at high risk of head injuries, including skull fractures, focal brain injuries, intracranial bleeding and diffuse brain injuries. New helmet technologies have been developed to mitigate head injuries in motorcycle collisions, but there is limited information on their performance under commonly occurring oblique impacts. We used an oblique impact method to assess the performance of seven modern motorcycle helmets at five impact locations. Four helmets were fitted with rotational management technologies: a low friction layer (MIPS), three-layer liner system (Flex) and dampers-connected liner system (ODS). Helmets were dropped onto a 45° anvil at 8 m/s at five locations. We determined peak translational and rotational accelerations (PTA and PRA), peak rotational velocity (PRV) and brain injury criteria (BrIC). In addition, we used a human head finite element model to predict strain distribution across the brain and in corpus callosum and sulci. We found that the impact location affected the injury metrics and brain strain, but this effect was not consistent. The rear impact produced lowest PTAs but highest PRAs. This impact produced highest strain in corpus callosum. The front impact produced the highest PRV and BrIC. The side impact produced the lowest PRV, BrIC and strain across the brain, sulci and corpus callosum. Among helmet technologies, MIPS reduced all injury metrics and brain strain compared with conventional helmets. Flex however was effective in reducing PRA only and ODS was not effective in reducing any injury metrics in comparison with conventional helmets. This study shows the importance of using different impact locations and injury metrics when assessing head protection effects of helmets. It also provides new data on the performance of modern motorcycle helmets. These results can help with improving helmet design and standard and rating test methods.

Incorporating neck biomechanics in helmet testing: Evaluation of commercially available WaveCel helmets

BACKGROUND

Cycling helmets often incorporate elements aimed to dissipate rotational energies, which is widely acknowledged to play a key role in concussion mechanics. In this study, we investigated the mechanics of an oblique helmet test protocol that induced helmet rotation while using it to evaluate the effectiveness of three helmet models: two standard expanded polystyrene helmets and a commercially-available helmet equipped with a liner designed to mitigate linear and rotational energies.

METHODS

Helmets equipped with WaveCel were tested against two expanded polystyrene helmet models through guided drops using a Hybrid III (HIII) head-and-neck surrogate. The three helmet models were tested across four impact conditions (n = 5) of different speeds and impact surface angles.

FINDINGS

Across all tests, a similar sequence of head motion was observed - first a flexion phase followed by an extension phase. The extension phase lacked evidence of biofidelity and was likely attributable to the energy stored in the neckform during the flexion phase; it was therefore neglected from analysis. Results showed WaveCel reduced the probability of AIS2 head injury across all tests (3 to 27% reductions in 4.8 m/s impacts; 36 to 37% reductions in 6.2 m/s impacts).

INTERPRETATION

The two-phased response of the HIII suggests that boundary condition selection can influence results and should thus be reported in studies using similar methods. While this protocol involved both axial and tangential impact components and were thus representative of real-world collisions, the efficacy of WaveCel should be further investigated through additional laboratory studies and tracking real-world cycling injury statistics.

Incidence of Electric Scooter-Associated Injuries in Finland From 2019 to 2021

This cross-sectional study examines the incidence of injuries associated with the use of electric scooters in Finland.