A typical gait analysis requires the examination of the motion of nine joint angles on the left-hand side and six joint angles on the right-hand side across multiple subjects. Due to the quantity and complexity of the data, it is useful to calculate the amount by which a subject's gait deviates from an average normal profile and to represent this deviation as a single number. Such a measure can quantify the overall severity of a condition affecting walking, monitor progress, or evaluate the outcome of an intervention prescribed to improve the gait pattern. The gait deviation index, gait profile score, and the overall abnormality measure are standard benchmarks for quantifying gait abnormality. However, these indices do not account for the intrinsic smoothness of the gait movement at each joint/plane and the potential co-variation between the joints/planes. Utilizing a multivariate functional principal components analysis we propose the functional gait deviation index (FGDI). FGDI accounts for the intrinsic smoothness of the gait movement at each joint/plane and the potential co-variation between the joints. We show that FGDI scales with overall gait function, provides a consistent measure of gait abnormality, and is implemented easily using an interactive web app.

翻译：典型的步态分析需要检查多名受试者左侧九个关节角度和右侧六个关节角度的运动。由于数据量庞大且复杂，计算受试者步态偏离平均正常曲线的程度并将其表示为单一数值非常有用。此类指标可量化影响行走能力的疾病总体严重程度、监测进展或评估旨在改善步态模式的干预效果。步态偏差指数、步态轮廓评分和总体异常度指标是量化步态异常的标准基准。然而，现有指标未考虑各关节/平面的步态运动固有平滑性及关节间的潜在协变关系。通过使用多元函数主成分分析，我们提出了功能性步态偏差指数（FGDI）。FGDI 既考虑了各关节/平面步态运动的固有平滑性，也兼顾了关节间的潜在协变关系。研究表明，FGDI 与整体步态功能呈正相关，能提供步态异常的一致度量，并可通过交互式网络应用程序轻松实现。