Development of a repetitive traumatic brain injury risk function based on real-world accident reconstruction and wavelet packet energy analysis - Xiong, Tao; Luo, Qinghang; Chen, Qiuju; Shi, Liangliang; Duan, Aowen; Liu, Shengxiong; Li, Kui (Frontiers in Bioengineering and Biotechnology, 2025)
Existing evaluation criteria for pedestrian head impact injuries focus only on single impacts, with less attention given to repetitive traumatic brain injury (rTBI), which is common in motor vehicle collisions, falls, and sports. Improving pedestrian collision protection safety requires a complete understanding of the tolerance of the repeated collisions of the human brain to injury. Therefore, this study aimed to collect data from 72 pedestrian collisions that were reconstructed using MADYMO and THUMS finite element head models (version 4.0.2). The evaluation metrics for rTBI were developed by integrating brain injury criteria based on time-domain features, including the head injury criterion (HIC), brain injury criterion (BrIC), diffuse axonal multi-axial general evaluation (DAMAGE), and maximum principal strain (MPS), with frequency-domain features obtained from wavelet packet transform energy analysis of head motion responses. The proposed brain tolerance for mild and severe rTBI was estimated through parametric survival analysis and presented as injury risk curves based on the selected injury metrics. The results showed a significant difference in brain injury tolerance between repetitive and single collisions. For the 50% probability of mild and severe brain injury in real accidents, the thresholds for rTBI metrics based on BrIC and DAMAGE were 1.085 and 1.513 and 0.494 and 0.678, respectively, all higher than the thresholds of single-impact reported in previous studies. However, the thresholds for repetitive head injury criteria based on MPS were 0.604 and 0.838, which were lower than the thresholds of single impact reported in previous studies, implying that the prediction of tolerance to repetitive brain more consistent with tissue-level than head kinematics level. This study developed injury risk functions (IRFs) for rTBI by integrating the amplitude–frequency characteristics of head responses and brain injury criteria. This knowledge further provides crucial support for understanding the tolerance to rTBI and enhancing pedestrian safety.