使用基于模拟的观察步态分析评估步行潜在生物力学目标的风格差异。

McKenna C Everett, Wentao Li, Ann Majewicz Fey, Nicholas P Fey
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引用次数: 0

摘要

观察性步态分析和分类评级通常被临床医生用于评估病理。本研究的目的是确定新手观察者使用风格标签描述生物力学性能目标下的步态行为的能力。我们假设,基于物理的步行肌肉骨骼预测模拟的视觉特征将对个体采用的生物力学目标以及视觉视角敏感。我们开发了75个全身肌肉驱动的预测步态仿真视频,分别对应5个受试者模型、5个生物力学目标和3个视觉视角。受试者模型被构建为五个人进行直线行走,并使用计算机肌肉控制为每个人生成最佳跟踪模拟。通过直接搭配,将五个不同的目标应用于每个个体的名义行为,包括代谢成本、肌肉激活的总和和平方、时间积分全身角动量、时间积分双边地面反作用力,以及一个等量加权的多目标成本函数。100名人群工作人员使用与每个目标对应的风格标签,以1-5的等级描述每个模拟。多项逻辑回归分析显示,负荷和激活等级是肌肉激活优化动作的显著预测因子,而激活等级是运动视角的显著预测因子。平衡性评分仅在正面视图中很重要,这表明平衡性指标在正面视图中更容易区分。总的来说,群体的智慧可以区分与一些生物力学目标相关的运动,但由于个体使用的运动控制策略的冗余,这种观察方法的分辨率是有限的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing Stylistic Differences in the Underlying Biomechanical Objectives of Walking Using Simulation-Based Observational Gait Analysis.

Observational gait analysis and categorical ratings are commonly used by clinicians to assess pathologies. The purpose of this study was to determine the capacity of novice observers to characterize the gait behavior underlying biomechanical performance objectives using stylistic labels. We hypothesized that visual characterization of physics-based musculoskeletal predictive simulations of walking would be sensitive to the biomechanical objective employed by individuals, as well as the visual perspective. We developed 75 full-body muscle-driven predictive gait simulation videos, corresponding to five subject models, five biomechanical objectives, and three visual perspectives. Subject models were constructed for five individuals performing straight line walking, with optimal tracking simulations generated for each using computed muscle control. Direct collocation was used to apply five different objectives to each individual's nominal behavior including metabolic cost, summed and squared muscle activations, time-integrated whole-body angular momentum, time-integrated bilateral ground reaction forces, and an equally weighted multi-objective cost function summing the individual objectives. 100 crowd workers characterized each simulation on a 1-5 scale using stylistic labels corresponding to each objective. Multinomial logistic regression analysis revealed that loading and activation ratings were significant predictors of muscle activation-optimized movements, while activation ratings were significant predictors of movement perspective. Balance ratings were significant for the frontal view alone, suggesting that balance indicators are more easily distinguished in the frontal plane. Collectively, the wisdom of crowds could distinguish motion associated with some biomechanical objectives, but due to the redundancy of motor control strategies used by individuals, the resolution of this observational approach is limited.

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