The burden of unhelmeted motorcycle injury: A nationwide scoring-based analysis of helmet safety legislation

Ganga, Arjun; Kim, Eric J.; Tang, Oliver Y.; Feler, Joshua; Sastry, Rahul; Anderson, Matthew N.; Keith, Sharonda E.; Fridley, Jared; Gokaslan, Ziya L.; Cielo, Deus J.; Toms, Steven; Sullivan, Patricia Zadnik

doi:10.1016/j.injury.2023.01.013

Cited by 3 publications

(1 citation statement)

References 42 publications

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“…Consequently, the mortality rate for bicycle and electric bicycle accidents has risen from 4.86% in 2000 to 6.97% in 2019 [ 1 ]. Meanwhile, in the United States, the fatality rate for motorcyclists in traffic accidents is 28 times higher than that of passengers in cars, a statistic that will reach concerning levels in 2020 [ 2 ]. Brain injury is the primary cause of the majority of these accidents are caused by brain injuries.…”

Section: Introductionmentioning

confidence: 99%

Lightweight helmet target detection algorithm combined with Effici-Bi-Level Routing Attention

Huang,

Fang,

Peng

2024

PLoS ONE

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Wearing helmets is essential in two-wheeler traffic to reduce the incidence of injuries caused by accidents. We present FB-YOLOv7, an improved detection network based on the YOLOv7-tiny model. The objective of this network is to tackle the problems of both missed detection and false detection that result from the difficulties in identifying small targets and the constraints in equipment performance during helmet detection. By applying an enhanced Bi-Level Routing Attention, the network can improve its capacity to extract global characteristics and reduce information distortion. Furthermore, we deploy the AFPN framework and effectively resolve information conflict using asymptotic adaptive feature fusion technology. Incorporating the EfficiCIoU loss significantly improves the prediction box’s accuracy. Experimental trials done on specific datasets reveal that FB-YOLOv7 attains an accuracy of 87.2% and 94.6% on the mean average precision (mAP@.5). Additionally, it maintains a high level of efficiency with frame rates of 129 and 126 frames per second (FPS). FB-YOLOv7 surpasses the other six widely-used detection networks in terms of detection accuracy, network implementation requirements, sensitivity in detecting small targets, and potential for practical applications.

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Section: Introductionmentioning

confidence: 99%

Lightweight helmet target detection algorithm combined with Effici-Bi-Level Routing Attention

Huang,

Fang,

Peng

2024

PLoS ONE

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Do the two-wheeler safety harnesses effective in rider’s safety – Analysis of attitude and switching intention

Sharma,

Sharma

et al. 2024

Case Studies on Transport Policy

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Facial Lacerations Related to Recreational Activities: A National 10-Year Evaluation From US Emergency Departments

Hauc,

Huelsboemer,

Lewis

et al. 2023

Craniomaxillofacial Trauma & Reconstruction

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Study Design This study serves as a nationally representative retrospective cohort of U.S emergency department visits related to facial lacerations caused by recreational activities. Objective The aim of this work is to offer a representative sample of facial laceration and identify the recreational activities associated with the highest risk of such injuries. Methods We conducted aretrospectivestudy of patients reported to the National Electronic Injury Surveillance System (NEISS) which collects information on injuries related to consumer products. Patients were included in our dataset from the time period of 2012 to 2021 if they sustained a facial laceration that was caused by a recreational activity. Results Our findings reveal 2,383,761 facial lacerations between the study period examined. Young male white adults were more likely to sustain a facial laceration related to recreational activities. Injuries related to exercise equipment were also more likely seen in male patients. The most common cause of facial lacerations was associated with bicycles and basketball. Conclusions This study found that young white adults are notably prone to facial lacerations, with recreational activities such as bicycling and basketball accounting for the majority of cases. Understanding these statistics is pivotal for implementing targeted strategies to prevent these injuries and their associated consequences.

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The burden of unhelmeted motorcycle injury: A nationwide scoring-based analysis of helmet safety legislation

Cited by 3 publications

References 42 publications

Lightweight helmet target detection algorithm combined with Effici-Bi-Level Routing Attention

Lightweight helmet target detection algorithm combined with Effici-Bi-Level Routing Attention

Do the two-wheeler safety harnesses effective in rider’s safety – Analysis of attitude and switching intention

Facial Lacerations Related to Recreational Activities: A National 10-Year Evaluation From US Emergency Departments

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