IEEE Trans Neural Syst Rehabil Eng. 2021;29:508-516. doi: 10.1109/TNSRE.2021.3057877. Epub 2021 Mar 2.
Previous work has shown that it is possible to use a mechanical phase variable to accurately quantify the progression through a human gait cycle, even in the presence of disturbances. However, mechanical phase variables are highly dependent on the behavior of the body segment from which they are measured, which can change with the human's task or in response to different disturbances. In this study, we compare kinematic parameterization methods based on time, thigh phase angle, and tibia phase angle with motion capture data obtained from ten able-bodied subjects walking at three inclines while experiencing phase-shifting perturbations from a split-belt instrumented treadmill. The belt, direction, and timings of perturbations were quasi-randomly selected to prevent anticipatory action by the subjects and sample different types of perturbations. Statistical analysis revealed that both phase parameterization methods are superior to time parameterization, with thigh phase angle also being superior to tibia phase angle in most cases.
先前的工作表明，即使存在干扰，使用机械相位变量也可以准确地量化人体步态周期的进展。然而，机械相位变量高度依赖于它们所测量的身体部位的行为，而这些行为可能会随着人体的任务或对不同干扰的反应而发生变化。在这项研究中，我们将基于时间、大腿相位角和胫骨相位角的运动学参数化方法与从十个健康受试者在三种倾斜度下行走时从分带式仪器化跑步机获得的运动捕捉数据进行比较，受试者在行走时经历相位移动干扰。带、方向和干扰的时间是准随机选择的，以防止受试者的预期动作，并采样不同类型的干扰。统计分析表明，两种相位参数化方法都优于时间参数化方法，在大多数情况下，大腿相位角也优于胫骨相位角。
