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首页> 外文期刊>Gait & posture >Principal Component Analysis of gait in Parkinson's disease: relevance of gait velocity.
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Principal Component Analysis of gait in Parkinson's disease: relevance of gait velocity.

机译：帕金森氏病步态的主要成分分析：步态速度的相关性。

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摘要

Principal Component Analysis (PCA) is a method to estimate the relation between data points. We used PCA to analyse movements of the upper and lower extremities during treadmill walking in healthy subjects and two groups of Parkinsonian patients. Healthy subjects (n=35) showed a typical pattern with high values of PC1 and low values in a descending order of PC2-PC4. Increase of speed resulted in a significant increase of PC1 and a significant decrease of the following PC's. In more severely affected patients (n=19, UPDRS>20), PC1 was significantly decreased and PC2-PC4 were significantly increased compared to healthy subjects. Speed could be increased only within a small range without corresponding changes of the PC's. In less severely affected patients (n=17), significant differences of the PC's were only found with fast pace. Separate analysis of arms and legs revealed that these changes are only due to altered movements of the arm. Analysis of the pattern of PC's in response to changes of gait velocities reveal alterations even in less severely affected Parkinsonian patients. The changes of the PC's with higher gait velocities in healthy subjects are suggestive of an increase of intersegmental coordination. This is impaired even in less severely affected Parkinsonian patients.
机译：主成分分析（PCA）是一种估计数据点之间关系的方法。我们使用PCA分析了健康受试者和两组帕金森病患者在跑步机上行走过程中上下肢的运动。健康受试者（n = 35）表现出典型的模式，PC1值高而PC2-PC4降序低。速度的提高导致PC1的显着增加，随后的PC的显着减少。与健康受试者相比，在受更严重影响的患者中（n = 19，UPDRS> 20），PC1显着降低，PC2-PC4显着升高。速度只能在很小的范围内增加，而不会相应地改变PC的速度。在病情较轻的患者（n = 17）中，仅以快速的步伐发现了PC的显着差异。对手臂和腿部进行单独分析后发现，这些变化仅是由于手臂运动的改变引起的。对步态速度变化做出反应的PC模式的分析显示，即使在受影响较轻的帕金森病患者中，其变化也是如此。在健康受试者中步态速度较高的PC的变化提示了节间协调的增加。即使在受影响较轻的帕金森病患者中，这种情况也会受损。

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