Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia.
Traffic Inj Prev. 2021;22(6):478-482. doi: 10.1080/15389588.2021.1929943. Epub 2021 Jun 17.
Although bicycle helmets are an effective countermeasure against head injury, many cyclists do not wear one. One avenue for facilitating widespread helmet use is through community-driven helmet safety initiatives, which often give away or subsidize wholesale helmet models that are manufactured at a low price point. However, the impact performance of such helmets during real-world accident conditions has yet to be explored. The present study seeks to investigate trends between wholesale bicycle helmet price and protective capabilities.
Nine common wholesale helmet models (price range $3.65-$12.95) were evaluated according to the bicycle Summation of Tests for the Analysis of Risk (STAR) methodology, which analyzes helmet performance in 24 oblique impact tests reflecting common cyclist head impact conditions. Resulting head peak linear acceleration (PLA) and peak rotational velocity (PRV) were collected and used to predict risk of concussion. Concussion risks were then combined using the STAR algorithm in order to summarize each model's risks into a single, weighted metric.
Large ranges in kinematic results led to large variations in concussion risks between helmets, and in turn, large variations in STAR values (13.5-26.2). Wholesale helmet price was not significantly associated with STAR, although incorporating 30 previous bicycle helmet STAR results produced a weak negative correlation between price and STAR overall. Nonetheless, the best-performing wholesale helmet produced one of the lowest overall STAR values for a price of $6.45. Helmet style was instead a superior predictor of STAR, with multi-sport style helmets producing significantly higher linear accelerations and resulting STAR values than bike style helmets.
These results show that the impact performance of wholesale helmets ranges considerably despite their low price-points. Results can also guide helmet safety promotion organizers toward distributing wholesale bicycle helmet models associated with lower overall concussion risks.
虽然自行车头盔是防止头部受伤的有效措施,但许多骑自行车的人并不佩戴。促进广泛使用头盔的一种途径是通过社区驱动的头盔安全倡议,这些倡议通常会赠送或补贴以低价制造的批量头盔模型。然而,这些头盔在现实事故条件下的冲击性能尚未得到探索。本研究旨在调查批发自行车头盔价格与保护能力之间的趋势。
根据自行车综合测试风险分析(STAR)方法评估了 9 种常见的批发头盔模型(价格范围为 3.65-12.95 美元),该方法分析了 24 个倾斜冲击测试中头盔的性能,这些测试反映了常见的骑车人头部冲击条件。收集产生的头部峰值线性加速度(PLA)和峰值旋转速度(PRV),并用于预测脑震荡风险。然后使用 STAR 算法组合脑震荡风险,以便将每个模型的风险汇总为单个加权指标。
运动学结果的大范围差异导致头盔之间的脑震荡风险差异很大,进而导致 STAR 值的差异很大(13.5-26.2)。批发头盔价格与 STAR 无显著相关性,尽管纳入 30 个先前的自行车头盔 STAR 结果,使价格与 STAR 之间呈微弱负相关。然而,表现最好的批发头盔以 6.45 美元的价格产生了最低的整体 STAR 值之一。头盔样式反而成为 STAR 的更好预测指标,多运动样式头盔产生的线性加速度和相应的 STAR 值明显高于自行车样式头盔。
这些结果表明,尽管批发头盔的价格低廉,但它们的冲击性能差异很大。结果还可以指导头盔安全推广组织分发与整体脑震荡风险较低相关的批发自行车头盔模型。