Department of Physical Therapy, University of Utah, Salt Lake City, UT, USA; Biomechanics Advanced, Encinitas, CA, USA.
Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
J Biomech. 2024 May;168:112075. doi: 10.1016/j.jbiomech.2024.112075. Epub 2024 Apr 4.
Whole-body angular momentum (WBAM) represents the cancellations of angular momenta that are produced during a reciprocal gait pattern. WBAM is sensitive to small changes and is used to compare dynamic gait patterns under different walking conditions. Study designs and the normalization techniques used to define WBAM vary and make comparisons between studies difficult. To address this problem, WBAM about each anatomical axis of rotation from a healthy control population during normal gait were investigated within four metrics: 1) range of WBAM, 2) integrated WBAM, 3) statistical parametric mapping (SPM), and 4) principal component analysis (PCA). These data were studied as a function of walking speed and normalization. Normalization techniques included: 1) no normalization, 2) normalization by height, body mass and walking speed, and 3) normalization by height, body mass and a scalar number, gravity×height, that is independent of walking velocity. Significant results were obtained as a function of walking speed regardless of normalization technique. However, the interpretation of significance within each metric was dependent on the normalization technique. Method 3 was the most robust technique as the differences were not altered from the expected relationships within the raw data. Method 2 actually inverted the expected relationship in WBAM amplitude as a function of walking speed, which skewed the results and their interpretation. Overall, SPM and PCA statistical methods provided better insights into differences that may be important. However, depending on the normalization technique used, caution is advised when interpreting significant findings when comparing participants with disparate walking speeds.
整体角动量（WBAM）代表了在反向步态模式中产生的角动量的抵消。WBAM 对小的变化很敏感，用于比较不同行走条件下的动态步态模式。研究设计和用于定义 WBAM 的归一化技术各不相同，使得难以进行研究之间的比较。为了解决这个问题，在四个指标内研究了正常步态下每个解剖旋转轴的 WBAM：1）WBAM 范围，2）整合 WBAM，3）统计参数映射（SPM），4）主成分分析（PCA）。这些数据作为行走速度和归一化的函数进行研究。归一化技术包括：1）无归一化，2）按身高、体重和行走速度归一化，3）按身高、体重和与行走速度无关的标量数，重力×高度归一化。无论归一化技术如何，都可以获得与行走速度相关的显著结果。然而，在每个指标内，显著性的解释取决于归一化技术。方法 3 是最稳健的技术，因为差异没有从原始数据中预期的关系发生改变。方法 2 实际上反转了 WBAM 幅度与行走速度之间的预期关系，从而扭曲了结果及其解释。总体而言，SPM 和 PCA 统计方法提供了对可能很重要的差异的更好理解。然而，根据使用的归一化技术，当比较行走速度不同的参与者时，在解释显著发现时需要谨慎。
