Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:926-932. doi: 10.1109/EMBC48229.2022.9871620.
Repetitive exposure to non-concussive blast expo-sure may result in sub-clinical neurological symptoms. These changes may be reflected in the neural control gait and balance. In this study, we collected body-worn accelerometry data on individuals who were exposed to repetitive blast overpressures as part of their occupation. Accelerometry features were gener-ated within periods of low-movement and gait. These features were the eigenvalues of high-dimensional correlation matrices, which were constructed with time-delay embedding at multiple delay scales. When focusing on the gait windows, there were significant correlations of the changes in features with the cumulative dose of blast exposure. When focusing on the low-movement frames, the correlation with exposure were lower than that of the gait frames and statistically insignificant. In a cross-validated model, the overpressure exposure was predicted from gait features alone. The model was statistically significant and yielded an RMSE of 1.27 dB. With continued development, the model may be used to assess the physiological effects of repetitive blast exposure and guide training procedures to minimize impact on the individual.
重复性非冲击性爆震暴露可能导致亚临床神经症状。这些变化可能反映在神经控制步态和平衡上。在这项研究中，我们收集了作为其职业一部分而暴露于重复性爆震超压下的个体的穿戴式加速度计数据。在低运动和步态期间生成了加速度计特征。这些特征是高维相关矩阵的本征值，这些矩阵是通过在多个延迟尺度上的时滞嵌入构建的。当专注于步态窗口时，特征变化与爆震暴露的累积剂量之间存在显著相关性。当专注于低运动帧时，与暴露的相关性低于步态帧，且无统计学意义。在交叉验证模型中，仅从步态特征即可预测超压暴露。该模型具有统计学意义，其均方根误差为 1.27 dB。随着进一步的开发，该模型可用于评估重复性爆震暴露的生理影响，并指导训练程序，以尽量减少对个体的影响。
