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校正算法对膝骨关节炎患者步态期间膝关节运动学和动力学的影响。

The Effect of Correction Algorithms on Knee Kinematics and Kinetics during Gait of Patients with Knee Osteoarthritis.

作者信息

Ulbricht Hanna, Hou Meijin, Wang Xiangbin, He Jian, Zhang Yanxin

机构信息

Human Movement Science, Chemnitz University of Technology, Chemnitz 09112, Germany.

Department of Exercise Sciences, University of Auckland, Auckland 1142, New Zealand.

出版信息

Appl Bionics Biomech. 2020 Nov 23;2020:8854124. doi: 10.1155/2020/8854124. eCollection 2020.

Abstract

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.

摘要

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。本研究的目的是确定两种现有算法在病理条件下对膝关节轴校正的有效性。使用运动捕捉系统收集了20名健康参与者和20名膝关节骨关节炎(OA)患者的步态数据。基于主成分分析(PCA)的算法和基于功能关节的算法(FJA)被用于定义膝关节屈曲轴。结果表明,PCA降低了两组的串扰,而FJA仅降低了膝关节OA患者的串扰。PCA显著降低了膝关节OA患者在外展/内收方向的运动范围。FJA使膝关节OA患者的最大膝关节屈曲力矩显著增加。结果表明,两种算法都能有效减少膝关节OA患者步态的串扰,这可能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关节OA患者的临床步态分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/578a/7707963/a2539a0efb1d/ABB2020-8854124.001.jpg

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