Determining fall direction and impact location for various disturbances and gait speeds using the articulated total body model.
Determining fall direction and impact location for various disturbances and gait speeds using the articulated total body model.
复制标题
使用铰接式全身模型确定各种干扰和步态速度的跌倒方向和冲击位置。
DOI：
10.1115/1.2737432
复制
发表时间：
2007
期刊：
影响因子：
--
通讯作者：
McMahon,ThomasA
中科院分区：
文献类型：
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作者：
Smeesters,Cecile;Hayes,WilsonC;McMahon,ThomasA
由于志愿者的跌倒实验既有挑战性又有风险，特别是老年志愿者，我们希望开发福尔斯的计算机模拟，为理解和扩展实验结果提供理论框架。为了对被动福尔斯的关节式全身（ATB）模型进行初步验证，我们将模型预测的跌倒方向、碰撞位置和碰撞速度作为干扰类型（昏厥、滑倒、踩下、绊倒）和步态速度（快、正常、慢）的函数与年轻成年志愿者的实验结果进行了比较。ATB三维模型包括17个节段和16个关节。它的物理特性、环境定义、接触函数和初始条件代表了我们的实验。对于扰动和步态速度的每种组合，ATB模型在受到扰动后在重力下被动下落，即，在与地板发生碰撞之前，不施加接头扭矩。最后，我们还确定了模型预测对模型参数变化的敏感性。我们的模型预测的下落角和冲击角定性与实验观察到的12个原始模拟中的10个和7个，分别。从数量上看，模型预测的坠落角度、撞击角度和撞击速度分别在12个原始模拟中的7个、3个和9个的一个实验标准差内，并且分别在12个原始模拟中的10个、9个和11个的两个实验标准差内。最后，在74次输入变化模拟中，分别有92%和95%的下落角和撞击角区域没有变化，而在74次输入变化模拟中，有78%的撞击速度在实验标准偏差范围内。基于我们的模拟和灵敏度分析，我们得出结论，我们的被动福尔斯的ATB模型的初步验证是成功的。事实上，这些ATB模型模拟代表了秋季模拟的重要一步。我们相信，通过进一步的工作，ATB模型可以用来准确地模拟各种人类福尔斯，并可能有助于进一步了解跌倒损伤，如髋部骨折的病因和机制。
Because fall experiments with volunteers can be both challenging and risky, especially with older volunteers, we wished to develop computer simulations of falls to provide a theoretical framework for understanding and extending experimental results. To perform a preliminary validation of the articulated total body (ATB) model for passive falls, we compared the model predictions of fall direction, impact location, and impact velocity as a function of disturbance type (faint, slip, step down, trip) and gait speed (fast, normal, slow) to experimental results with young adult volunteers. The three-dimensional ATB model had 17 segments and 16 joints. Its physical characteristics, environment definitions, contact functions, and initial conditions were representative of our experiment. For each combination of disturbance and gait speed, the ATB model was left to fall passively under gravity once disturbed, i.e., no joint torques were applied, until impact with the floor occurred. Finally, we also determined the sensitivity of the model predictions to changes in the model’s parameters. Our model predictions of fall angles and impact angles were qualitatively in agreement with those observed experimentally for ten and seven of the 12 original simulations, respectively. Quantitatively, the model predictions of fall angles, impact angles, and impact velocities were within one experimental standard deviation for seven, three, and nine of the 12 original simulations, respectively, and within two experimental standard deviations for ten, nine, and 11 of the 12 original simulations, respectively. Finally, the fall angle and impact angle region did not change for 92% and 95% of the 74 input variation simulations, respectively, and the impact velocities were within the experimental standard deviations for 78% of the 74 input variation simulations. Based on our simulations and a sensitivity analysis, we conclude that our preliminary validation of the ATB model for passive falls was successful. In fact, these ATB model simulations represent a significant step forward in fall simulations. We believe that with additional work, the ATB model could be used to accurately simulate a variety of human falls and may be useful in further understanding the etiology and mechanisms of fall injuries such as hip fractures.