The combined gait asymmetry metric (CGAM) provides a method to synthesize human gait motion. The metric is weighted to balance each parameter’s effect by normalizing the data so all parameters are more equally weighted. It is designed to combine spatial, temporal, kinematic, and kinetic gait parameter asymmetries. It can also combine subsets of the different gait parameters to provide a more thorough analysis. The single number quantifying gait could assist robotic rehabilitation methods to optimize the resulting gait patterns. CGAM will help define quantitative thresholds for achievable balanced overall gait asymmetry. The study presented here compares the combined gait parameters with clinical measures such as timed up and go (TUG), six-minute walk test (6MWT), and gait velocity. The comparisons are made on gait data collected on individuals with stroke before and after twelve sessions of rehabilitation. Step length, step time, and swing time showed a strong correlation to CGAM, but the double limb support asymmetry has nearly no correlation with CGAM and ground reaction force asymmetry has a weak correlation. The CGAM scores were moderately correlated with TUG and strongly correlated to 6MWT and gait velocity.

中文翻译：

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用于步态再训练的人类步态分析指标。


组合步态不对称度量（CGAM）提供了一种合成人类步态运动的方法。通过对数据进行标准化，对指标进行加权，以平衡每个参数的影响，从而使所有参数的权重更加均等。它旨在结合空间、时间、运动学和动力学步态参数不对称性。它还可以组合不同步态参数的子集以提供更彻底的分析。单一数字量化步态可以帮助机器人康复方法优化最终的步态模式。 CGAM 将帮助定义可实现平衡的整体步态不对称的定量阈值。本文介绍的研究将组合步态参数与计时行走 (TUG)、六分钟步行测试 (6MWT) 和步态速度等临床测量值进行了比较。这些比较是对中风患者在十二次康复之前和之后收集的步态数据进行的。步长、步时和摆动时间与 CGAM 表现出较强的相关性，但双肢支撑不对称性与 CGAM 几乎没有相关性，地面反作用力不对称性具有弱相关性。 CGAM 评分与 TUG 中度相关，与 6MWT 和步态速度强相关。