Noamani Alireza, Vette Albert H, Preuss Richard, Popovic Milos R, Rouhani Hossein
Department of Mechanical Engineering, University of Alberta, Donadeo Innovation Centre for Engineering, Edmonton, Alberta, T6G 1H9, Canada.
Department of Mechanical Engineering, University of Alberta, Donadeo Innovation Centre for Engineering, Edmonton, Alberta, T6G 1H9, Canada; Glenrose Rehabilitation Hospital, Alberta Health Services, 10230 111 Avenue NW, Edmonton, Alberta, T5G 0B7, Canada.
Gait Posture. 2018 Jul;64:205-212. doi: 10.1016/j.gaitpost.2018.06.027. Epub 2018 Jun 18.
Motion assessment of the body's head-arms-trunk (HAT) using linked-segment models, along with an inverse dynamics approach, can enable in vivo estimations of inter-vertebral moments. However, this mathematical approach is prone to experimental errors because of inaccuracies in (i) kinematic measurements associated with soft tissue artifacts and (ii) estimating individual-specific body segment parameters (BSPs). The inaccuracy of the BSPs is particularly challenging for the multi-segment HAT due to high inter-participant variability in the HAT's BSPs and no study currently exists that can provide a less erroneous estimation of the joint moments along the spinal column.
This study characterized three-dimensional (3D) inter-segmental moments in a multi-segment HAT model during multi-directional trunk-bending, after minimizing the experimental errors.
Eleven healthy individuals participated in a multi-directional trunk-bending experiment in five directions with three speeds. A seven-segment HAT model was reconstructed for each participant, and its motion was recorded. After compensating for experimental errors due to soft tissue artifacts, and using optimized individual-specific BSPs, and center of pressure offsets, the inter-segmental moments were calculated via inverse dynamics.
Our results show a significant effect of the inter-segmental level and trunk-bending directions on the obtained moments. Compensating for soft tissue artifacts contributed significantly to reducing errors. Our results indicate complex, task-specific patterns of the 3D moments, with high inter-participant variability at different inter-segmental levels, which cannot be studied using single-segment models or without error compensation.
Interpretation of inter-segmental moments after compensation of experimental errors is important for clinical evaluations and developing injury prevention and rehabilitation strategies.
使用链接节段模型以及逆动力学方法对身体的头-臂-躯干（HAT）进行运动评估，可以实现体内椎间力矩的估计。然而，这种数学方法容易出现实验误差，原因在于：（i）与软组织伪影相关的运动学测量不准确；（ii）估计个体特定的身体节段参数（BSP）。由于HAT的BSP在参与者之间存在高度变异性，对于多节段HAT而言，BSP的不准确性尤其具有挑战性，并且目前尚无研究能够对脊柱关节力矩进行误差较小的估计。
本研究在将实验误差降至最低后，对多节段HAT模型在多方向躯干弯曲过程中的三维（3D）节段间力矩进行了表征。
11名健康个体参与了在五个方向、三种速度下进行的多方向躯干弯曲实验。为每位参与者重建了一个七节段HAT模型，并记录其运动。在补偿了软组织伪影导致的实验误差后，使用优化的个体特定BSP和压力中心偏移，通过逆动力学计算节段间力矩。
我们的结果表明，节段间水平和躯干弯曲方向对获得的力矩有显著影响。补偿软组织伪影对减少误差有显著作用。我们的结果表明，3D力矩呈现复杂的、特定任务的模式，在不同节段间水平存在较高的参与者间变异性，这是单节段模型或无误差补偿情况下无法研究的。
在补偿实验误差后对节段间力矩进行解释，对于临床评估以及制定损伤预防和康复策略具有重要意义。
