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使用平滑样条来推断气体交换曲线的形状。

Using smoothing splines to make inferences about the shape of gas-exchange curves.

作者信息

Wade T D, Anderson S J, Bondy J, Ramadevi V A, Jones R H, Swanson G D

机构信息

Department of Preventive Medicine and Biometrics, School of Medicine, University of Colorado Health Sciences Center, Denver 80262.

出版信息

Comput Biomed Res. 1988 Feb;21(1):16-26. doi: 10.1016/0010-4809(88)90038-9.

Abstract

Respiratory gas-exchange data from progressive exercise tests are typically interpreted by visual inspection. Attempts to objectify such interpretation have applied particular parametric models which limit the measures which can be studied and the inferences which can be made. We use a known spline-smoothing procedure which fits a continuous curve to such data, yielding confidence intervals for the curve and for its first and second derivatives. Rules can be made which use the derivatives to infer features of a curve's shape and to relate features from different curves in the same data set. In this way complex interpretations can be made objective, so that they may be adequately tested.

摘要

递增运动试验中的呼吸气体交换数据通常通过目视检查来解释。试图使这种解释客观化的尝试采用了特定的参数模型,这些模型限制了可以研究的测量指标以及可以得出的推论。我们使用一种已知的样条平滑程序,该程序将一条连续曲线拟合到这些数据上,从而得出曲线及其一阶和二阶导数的置信区间。可以制定规则,利用这些导数来推断曲线形状的特征,并关联同一数据集中不同曲线的特征。通过这种方式,可以使复杂的解释变得客观,从而可以对其进行充分的检验。

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