In gait analysis, the accuracy of knee joint angles and moments is critical for clinical decision-making. The purpose of this study was to determine the efficacy of two existing algorithms for knee joint axis correction under pathological conditions. Gait data from 20 healthy participants and 20 patients with knee osteoarthritis (OA) were collected using a motion capture system. An algorithm based on Principal Component Analysis (PCA) and a functional joint-based algorithm (FJA) were used to define the knee joint flexion axis. The results show that PCA decreased crosstalk for both groups, and FJA reduced crosstalk in patients with knee OA only. PCA decreased the range of motions of patients with knee OA in the direction of abduction/adduction significantly. There was a significant increase in the maximum knee flexion moment of patients with knee OA by FJA. The results indicate that both algorithms can efficiently reduce crosstalk for gait from patients with knee OA, which can further influence the results of knee joint angles and moments. We recommend that the correction algorithms be applied in clinical gait analysis with patients with knee OA.

中文翻译：

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校正算法对膝骨关节炎患者步态运动时膝关节运动学和动力学的影响

在步态分析中，膝关节角度和力矩的准确性对于临床决策至关重要。这项研究的目的是确定两种现有的病理条件下矫正膝关节轴的算法的有效性。使用运动捕捉系统收集了来自20位健康参与者和20位膝骨关节炎（OA）患者的步态数据。使用基于主成分分析（PCA）的算法和基于功能关节的算法（FJA）定义膝关节屈曲轴。结果表明，仅膝骨关节炎患者，PCA降低了两组的串扰，FJA降低了串扰。PCA显着降低了膝OA患者在外展/内收方向上的运动范围。FJA使膝骨关节炎患者的最大屈膝力矩显着增加。结果表明，两种算法都可以有效地减少来自膝骨关节炎患者步态的串扰，这可以进一步影响膝关节角度和力矩的结果。我们建议将校正算法应用于膝骨关节炎患者的临床步态分析中。