Towards representative testing of helmets

Over 69 million people are affected by traumatic brain injuries (TBIs)1 around the world. The cost to the global economy is estimated at £350 billion2. In the UK, TBI is the leading cause of death and disability in people under-forty with an annual economic burden of £15 billion3. These TBIs are mainly caused by falls, traffic accidents involving vulnerable road users (e.g., cyclists) and sport/recreation. Mild traumatic brain injuries (mTBIs), such as concussions, account for up to 90% of all TBI cases presenting to hospital and around 50% of adults take more than six months to fully recover2. Across many activities and occupations, helmets are used to reduce the risk of TBIs and in cycling for example, have been found to be most effective against moderate and severe TBIs4. However, making them effective against all severities of TBIs is a major challenge. Their design intent relies on scientific understanding of the underlying injury mechanisms and how to best represent them with test methods that allow for meaningful evaluations of the helmet’s performance to be measured. Current evaluation methods are limited in the following ways: real-world impact conditions that result in injury are rarely quantified; only head-first severe cases are represented and; the surrogates used do not adequately represent the human’s biomechanical response to impact. Significantly, the role of the neck and its influence on the head’s response is often not included. Therefore, the objective of this research is to make a significant step towards the realisation of next generation helmets through: quantifying impact conditions using real-world video and embedded sensor data; new test methods that represent the varied conditions of real-world collisions; digital twin services that enable manufacturers to evaluate new materials and designs prior to volume manufacture and; establishing the foundations of world-class testing facilities for helmet capability evaluations. Given the UK’s push towards active mobility with its associated health and wellbeing benefits and positive contribution to net zero carbon targets, this research will focus on cycling helmets. UK cycling participation has more than doubled compared with pre-COVID times, and is predicted to continue to grow. Cycling is however, a leading cause of mTBIs5 and with increased participation comes increased exposure to injury risk. To contribute towards effective helmet design, this research will address the shortcomings of current helmet evaluation methods. Firstly, it will use video and embedded helmet sensors to quantify impact parameters, as recommended in the 2022 Lancet Neurology Commissions on TBIs report2. Secondly, it will develop body-first test apparatus to evaluate helmet performance across the varied scenarios experienced in the real-world. Finally, it will use a biomechanically representative surrogate neck with tuneable posture, stiffness and range of motion to investigate the neck’s influence on rotational response of the head, which is commonly associated with mTBI risk5. This research will result in new test methods with appropriate representation of the real-world collision case. It will improve understanding of mTBI injury mechanisms and enable the development of targeted helmet technologies to protect against it. This project is timely and could reduce the socio-economic cost of TBIs on an international level. 1Dewan MC, et al. 2018; DOI: 10.3171/2017.10.JNS17352 2Lancet Neurology. 2022; DOI: 10.1016/S1474-4422(22)00309-X 3Parsonage M. Traumatic brain injury and offending: an economic analysis. Centre for mental health 4Sone et al. 2017; DOI: 10.3171/2016.2.JNS151972 5Bland et al. 2020; DOI: 10.1007/s10439-019-02330-0