Post-ACLR individuals can experience repeated exposure to variable limb loading, which contributes to development of knee osteoarthritis. Variable limb loading can present as loading rate variability (LRV) and is magnified during tasks like fast walking when the system is stressed. Nonlinear measures that evaluate temporal variability have successfully detected changes in gait variability associated with altered motor control, however, appropriately describing and uncovering the nature of gait variability has been challenging. Here, Poincaré analysis, a nonlinear method unique in its ability to capture different aspects of variability, served to uncover and quantify changes in limb LRV. It was hypothesized that post-ACLR individuals’ overloaded limbs would quantitatively and graphically demonstrate greater short-term stride-to-stride and long-term limb LRV during fast walking compared to the underloaded and healthy control limbs. Fourteen post-ACLR individuals and fourteen healthy controls completed a walking protocol on an instrumented treadmill where they walked at 1.0 m/s and 1.5 m/s for 5-minutes each. A Welch’s test was performed to compare differences in short-term and long-term LRV metrics for the post-ACLR individuals’ overloaded and underloaded limbs and the healthy controls’ right limbs. Analyses revealed that the post-ACLR individuals’ overloaded limb exhibited significantly greater short-term and long-term values compared to the underloaded and healthy control limbs at 1.5 m/s (p<0.05). Additionally, the loading rate data was widely scattered across the plots for the overloaded limb, indicating greater LRV. Poincaré analysis successfully identified that post-ACLR overloaded limbs exhibited impaired motor control during fast walking based on quantitative and graphical changes in variability. This highlights the clinical applications of Poincaré analysis, with the plots potentially serving as an easy-to-interpret diagnostic tool for pathological limb LRV.

中文翻译：

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庞加莱分析检测前十字韧带重建后个体的病理肢体负荷率变异性

ACLR 术后患者可能会反复承受可变的肢体负荷，这会导致膝骨关节炎的发生。可变的肢体负载可以表现为负载率变异性（LRV），并且在系统承受压力时快速行走等任务中会被放大。评估时间变异性的非线性测量已成功检测到与运动控制改变相关的步态变异性变化，然而，正确描述和揭示步态变异性的本质一直具有挑战性。庞加莱分析是一种非线性方法，能够捕捉不同方面的变异性，可用于揭示和量化肢体 LRV 的变化。据推测，与负载不足和健康的对照肢体相比，ACLR 后个体超载的肢体将在快速步行过程中以定量和图形方式显示出更大的短期步幅和长期肢体 LRV。 14 名接受 ACLR 治疗的个体和 14 名健康对照者在仪器跑步机上完成了步行方案，他们以 1.0 m/s 和 1.5 m/s 的速度各行走 5 分钟。进行 Welch 测试来比较 ACLR 后个体超载和欠载四肢以及健康对照右肢的短期和长期 LRV 指标的差异。分析显示，在 1.5 m/s 速度下，与负载不足和健康对照肢体相比，ACLR 后个体的过载肢体表现出显着更大的短期和长期值 (p<0.05)。此外，负载率数据广泛分散在超载肢体的各个图中，表明 LRV 更大。庞加莱分析根据变异性的定量和图形变化，成功识别出 ACLR 后超负荷的肢体在快走过程中表现出运动控制受损。这突出了庞加莱分析的临床应用，该图有可能作为病理肢体 LRV 的易于解释的诊断工具。