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使用生物电阻抗光谱法进行身体成分分析的电阻率系数:身体优势和混合理论算法的影响。

Resistivity coefficients for body composition analysis using bioimpedance spectroscopy: effects of body dominance and mixture theory algorithm.

作者信息

Ward L C, Isenring E, Dyer J M, Kagawa M, Essex T

机构信息

School Chemistry and Molecular Biosciences, The University of Queensland, Australia.

出版信息

Physiol Meas. 2015 Jul;36(7):1529-49. doi: 10.1088/0967-3334/36/7/1529. Epub 2015 Jun 2.

Abstract

Body composition is commonly predicted from bioelectrical impedance spectroscopy using mixture theory algorithms. Mixture theory algorithms require the input of values for the resistivities of intra-and extracellular water of body tissues. Various derivations of these algorithms have been published, individually requiring resistivity values specific for each algorithm. This study determined apparent resistivity values in 85 healthy males and 66 healthy females for each of the four published mixture theory algorithms. The resistivity coefficients determined here are compared to published values and the inter-individual (biological) variation discussed with particular reference to consequential error in prediction of body fluid volumes. In addition, the relationships between the four algorithmic approaches are derived and methods for the inter-conversion of coefficients between algorithms presented.

摘要

身体成分通常使用混合理论算法通过生物电阻抗光谱法来预测。混合理论算法需要输入身体组织细胞内液和细胞外液电阻率的值。这些算法有各种不同的推导版本,每个版本都各自需要特定的电阻率值。本研究针对四种已发表的混合理论算法,分别测定了85名健康男性和66名健康女性的表观电阻率值。将此处测定的电阻率系数与已发表的值进行比较,并特别参照预测体液量时的相应误差,讨论个体间(生物学)差异。此外,推导了四种算法方法之间的关系,并提出了算法之间系数相互转换的方法。

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