An application of principal component analysis for lower body kinematics between loaded and unloaded walking
An application of principal component analysis for lower body kinematics between loaded and unloaded walking
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DOI：
10.1016/j.jbiomech.2009.06.052
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发表时间：
2009-10-16
影响因子：
2.4
通讯作者：
Smith, Benjamin
中科院分区：
文献类型：
--
作者：
Lee, Minhyung;Roan, Michael;Smith, Benjamin
搬运在家里和工作场所是一项非常常见的日常活动。一般来说，负荷是由个人承担的外部负荷的形式，也可能是超重个人承担的过大的身体质量。为了量化携带额外体重的影响，无论是以外部负荷的形式还是以超重的身体质量的形式，为不同的受试者生成了运动捕捉数据，该受试组由23名受试者组成，为每种负荷条件产生115次试验。将主成分分析(PCA)应用于运动捕捉数据，分析了正常体重、正常体重、超重卸载和超重加载四种情况下的下半身步态模式，表明主成分分析是分析复杂步态数据的有力工具。在这一分析中，为了量化外部载荷的影响和/或对正常体重和超重受试者的影响，本文需要第一主成分(PC1)。第一主成分(PC1)是根据下半身关节角度数据生成的。髋角的PC1和踝角的PC1被证明是外部负荷和BMI对临时步态数据影响的指标，(C)2009爱思唯尔有限公司。保留所有权利。
Load carriage is a very common daily activity at home and in the workplace. Generally, the load is in the form of an external load carried by an individual, it could also be the excessive body mass carried by an overweight individual. To quantify the effects of carrying extra weight, whether in the form of an external load or excess body mass, motion capture data were generated for a diverse subject set This consisted of twenty-three subjects generating one hundred fifteen trials for each loading condition. This study applied principal component analysis (PCA) to motion capture data in order to analyze the lower body gait patterns for four loading conditions normal weight unloaded, normal weight loaded, overweight unloaded and overweight loaded.PCA has been shown to be a powerful tool for analyzing complex gait data. In this analysis, it is shown that in order to quantify the effects of external loads and/or for both normal weight and overweight subjects, the first principal component (PC1) is needed For the work in this paper, PCs were generated from lower body joint angle data. The PC1 of the hip angle and PC1 of the ankle angle are shown to be an indicator of external load and BMI effects on temporal gait data, (C) 2009 Elsevier Ltd. All rights reserved.