Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.
Dyson School of Design Engineering, Imperial College London, London, UK.
Ann Biomed Eng. 2022 Nov;50(11):1389-1408. doi: 10.1007/s10439-022-02999-w. Epub 2022 Jul 22.
Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.
头部加速度测量传感器现在广泛应用于监测接触性运动中头部运动暴露的领域。丰富的冲击运动学数据为研究轻度创伤性脑损伤（mTBI）和亚临床运动暴露的生物力学基础提供了有价值但具有挑战性的机会。通过使用经过验证的大脑模型进行基于物理的计算模拟，将头部冲击运动学转化为大脑机械响应，以研究损伤机制。本文首先回顾了主要用于钝性冲击模拟的代表性传统和当代大脑生物力学模型。然后，它总结了关于这些模型的开发和验证的观点，并讨论了如何解释模拟结果，以促进接触性运动中损伤风险评估和头部加速度暴露监测。本文提出了关于在接触性运动中使用经过验证的大脑模型结合运动传感器数据来理解 mTBI 和亚临床冲击运动暴露的生物力学的建议和共识声明。主要的共识是，经过验证的大脑模型具有通过全局头部运动学来提高损伤预测和解释亚临床冲击运动暴露的强大潜力。然而，实现这一能力的一个主要障碍是缺乏涵盖不同运动、性别、年龄和其他因素的足够数据。作者建议进一步整合传感器数据和模拟与现代数据科学技术，以生成暴露和预测大脑反应的大量数据集，以及相关的临床发现。这些努力有望帮助更好地理解 mTBI 的生物力学基础，并提高监测接触性运动中运动暴露的有效性，以降低风险和减少损伤。
