Kurt Mehmet, Laksari Kaveh, Kuo Calvin, Grant Gerald A, Camarillo David B
Department of Bioengineering, Stanford University, 443 Via Ortega, Shriram Bldg Room 202, Stanford, CA, 94305, USA.
Department of Mechanical Engineering, Stanford University, Stanford, CA, 94305, USA.
Ann Biomed Eng. 2017 Apr;45(4):1148-1160. doi: 10.1007/s10439-016-1732-1. Epub 2016 Sep 27.
Bicycling is the leading cause of sports-related traumatic brain injury. Most of the current bike helmets are made of expanded polystyrene (EPS) foam and ultimately designed to prevent blunt trauma, e.g., skull fracture. However, these helmets have limited effectiveness in preventing brain injuries. With the availability of high-rate micro-electrical-mechanical systems sensors and high energy density batteries, a new class of helmets, i.e., expandable helmets, can sense an impending collision and expand to protect the head. By allowing softer liner medium and larger helmet sizes, this novel approach in helmet design provides the opportunity to achieve much lower acceleration levels during collision and may reduce the risk of brain injury. In this study, we first develop theoretical frameworks to investigate impact dynamics of current EPS helmets and airbag helmets-as a form of expandable helmet design. We compared our theoretical models with anthropomorphic test dummy drop test experiments. Peak accelerations obtained from these experiments with airbag helmets achieve up to an 8-fold reduction in the risk of concussion compared to standard EPS helmets. Furthermore, we construct an optimization framework for airbag helmets to minimize concussion and severe head injury risks at different impact velocities, while avoiding excessive deformation and bottoming-out. An optimized airbag helmet with 0.12 m thickness at 72 ± 8 kPa reduces the head injury criterion (HIC) value to 190 ± 25 at 6.2 m/s head impact velocity compared to a HIC of 1300 with a standard EPS helmet. Based on a correlation with previously reported HIC values in the literature, this airbag helmet design substantially reduces the risks of severe head injury up to 9 m/s.
骑自行车是与运动相关的创伤性脑损伤的主要原因。目前大多数自行车头盔由发泡聚苯乙烯（EPS）泡沫制成，其最终设计目的是防止钝器创伤，例如颅骨骨折。然而，这些头盔在预防脑损伤方面效果有限。随着高速微机电系统传感器和高能量密度电池的出现，一种新型头盔，即可膨胀头盔，能够感知即将发生的碰撞并膨胀以保护头部。通过采用更柔软的内衬介质和更大的头盔尺寸，这种新颖的头盔设计方法有机会在碰撞过程中实现更低的加速度水平，并可能降低脑损伤风险。在本研究中，我们首先建立理论框架来研究当前EPS头盔和气囊头盔（作为可膨胀头盔设计的一种形式）的冲击动力学。我们将理论模型与人体模型跌落测试实验进行了比较。与标准EPS头盔相比，这些气囊头盔实验获得的峰值加速度使脑震荡风险降低了8倍。此外，我们构建了一个气囊头盔优化框架，以在不同冲击速度下将脑震荡和严重头部受伤风险降至最低，同时避免过度变形和触底。与标准EPS头盔的头部损伤标准（HIC）值为1300相比，在头部冲击速度为6.2 m/s时，厚度为0.12 m、压力为72±8 kPa的优化气囊头盔将HIC值降低至190±25。基于与文献中先前报道的HIC值的相关性，这种气囊头盔设计在高达9 m/s的速度下大幅降低了严重头部受伤的风险。
