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步态数据的全面无量纲归一化。

Comprehensive non-dimensional normalization of gait data.

作者信息

Pinzone Ornella, Schwartz Michael H, Baker Richard

机构信息

University of Salford, UK.

Gillette Children's Specialty Healthcare, St. Paul, MN, USA; University of Minnesota, Minneapolis, MN, USA.

出版信息

Gait Posture. 2016 Feb;44:68-73. doi: 10.1016/j.gaitpost.2015.11.013. Epub 2015 Dec 2.

Abstract

Normalizing clinical gait analysis data is required to remove variability due to physical characteristics such as leg length and weight. This is particularly important for children where both are associated with age. In most clinical centres conventional normalization (by mass only) is used whereas there is a stronger biomechanical argument for non-dimensional normalization. This study used data from 82 typically developing children to compare how the two schemes performed over a wide range of temporal-spatial and kinetic parameters by calculating the coefficients of determination with leg length, weight and height. 81% of the conventionally normalized parameters had a coefficient of determination above the threshold for a statistical association (p<0.05) compared to 23% of those normalized non-dimensionally. All the conventionally normalized parameters exceeding this threshold showed a reduced association with non-dimensional normalization. In conclusion, non-dimensional normalization is more effective that conventional normalization in reducing the effects of height, weight and age in a comprehensive range of temporal-spatial and kinetic parameters.

摘要

对临床步态分析数据进行归一化处理,是为了消除因腿长和体重等身体特征导致的变异性。这对儿童尤为重要,因为这两个因素都与年龄相关。在大多数临床中心,使用的是传统归一化方法(仅按体重),而从生物力学角度来看,无量纲归一化更具说服力。本研究使用了82名发育正常儿童的数据,通过计算与腿长、体重和身高的决定系数,比较了这两种方案在广泛的时空和动力学参数上的表现。与23%的无量纲归一化参数相比,81%的传统归一化参数的决定系数高于统计关联阈值(p<0.05)。所有超过该阈值的传统归一化参数与无量纲归一化的关联度都有所降低。总之,在减少身高、体重和年龄对一系列时空和动力学参数的影响方面,无量纲归一化比传统归一化更有效。

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