Mechanical Engineering Department, California Polytechnic State University, San Luis Obispo, CA 93407.
Mechanical Engineering Department, California Polytechnic State University, San Luis Obispo, CA 93407; Biomedical Engineering Department, California Polytechnic State University, San Luis Obispo, CA 93407.
J Biomech Eng. 2021 May 1;143(5). doi: 10.1115/1.4049809.
Principal component analysis (PCA) has been used as a post-hoc method for reducing knee crosstalk errors during gait analysis. PCA minimizes correlations between flexion-extension (FE), abduction-adduction (AA), and internal-external rotation (IE) angles. However, previous studies have not considered PCA for exercises involving knee flexion angles that are greater than those typically experienced during gait. Thus, the goal of this study was to investigate using PCA to correct for crosstalk during one exercise (i.e., cycling) that involves relatively high flexion angles. Fifteen participants were tested in gait and cycling using a motion analysis system. Uncorrected FE, AA and IE angles were compared to those calculated with PCA performed on (1) all angles (FE-AA-IE PCA correction) and (2) only FE-AA angles (FE-AA PCA correction). Significant differences existed between uncorrected and FE-AA-IE PCA corrected AA and IE angles for both exercises, between uncorrected and FE-AA PCA corrected AA angles for both exercises, and between FE-AA-IE and FE-AA PCA corrected IE angles for cycling. Correlations existed before PCA correction and were eliminated following PCA correction with the exception that FE-IE correlations remained following FE-AA PCA correction. Since the two PCA analyses differed only in their IE angle predictions for the high flexion exercise (cycling), IE angle results were compared to previous studies. Using FE-AA PCA correction may be the preferred protocol for cycling as it appeared to retain physiological IE angle correlations at high flexion angles. However, there exists a critical need for studies aimed at obtaining more accurate IE angles in such exercises.
主成分分析（PCA）已被用作步态分析中减少膝关节串扰误差的事后方法。PCA 最小化了屈伸（FE）、外展内收（AA）和内外旋转（IE）角度之间的相关性。然而，以前的研究并没有考虑到 PCA 在涉及膝关节屈曲角度大于步态时通常经历的运动中的应用。因此，本研究的目的是研究使用 PCA 来校正涉及相对较高屈曲角度的一项运动（即骑自行车）中的串扰。使用运动分析系统对 15 名参与者进行了步态和骑自行车测试。未校正的 FE、AA 和 IE 角度与通过以下两种方法计算的角度进行了比较：（1）所有角度（FE-AA-IE PCA 校正）和（2）仅 FE-AA 角度（FE-AA PCA 校正）。两种运动都存在未校正的 AA 和 IE 角度与 FE-AA-IE PCA 校正之间、两种运动都存在未校正的 AA 角度与 FE-AA PCA 校正之间、以及骑自行车时的 FE-AA-IE 和 FE-AA PCA 校正的 IE 角度之间存在显著差异。在进行 PCA 校正之前存在相关性，并且在进行 PCA 校正后消除了相关性，除了在进行 FE-AA PCA 校正后 FE-IE 相关性仍然存在。由于两种 PCA 分析仅在其对高屈曲运动（骑自行车）的 IE 角度预测方面有所不同，因此将 IE 角度结果与以前的研究进行了比较。使用 FE-AA PCA 校正可能是骑自行车的首选方案，因为它似乎在高屈曲角度下保留了生理 IE 角度相关性。然而，在这种运动中获得更准确的 IE 角度存在迫切需要。
Zotero 插件