Lanshammar H
J Biomech. 1982;15(2):99-105. doi: 10.1016/0021-9290(82)90041-0.
Numerical differentiation of noisy measurement data represents a problem frequently encountered in the field of gait analysis. There are two major determinants of the quality in calculated derivatives, namely the quality of the measurement data and the quality of the used differentiation technique. The quality of the measurement data, with respect to the maximum precision that can be obtained in calculated derivatives, is discussed with the help of an error formula valid for all differentiating techniques. It is verified that high precision can be obtained in the calculated second derivatives even with crude techniques, provided that the quality of the measurement data are good enough. This point is illustrated by the differentiation film data from Pezzack et al. (1977), using a least squares polynomial fitting. For the evaluation and comparison of different techniques for numerical differentiation it is recommended that measurement data with a considerable amount of noise is used, and that the quality of calculated derivatives are evaluated not only by visual inspection of graphical displays, but also with the use of a quantitative criteria, such as the root mean squares error.
对噪声测量数据进行数值微分是步态分析领域经常遇到的一个问题。计算导数的质量有两个主要决定因素,即测量数据的质量和所使用的微分技术的质量。借助一个对所有微分技术都有效的误差公式,讨论了测量数据的质量与计算导数中可获得的最大精度之间的关系。结果表明,只要测量数据的质量足够好,即使使用粗糙的技术,也能在计算的二阶导数中获得高精度。这一点通过佩扎克等人(1977年)的微分胶片数据进行了说明,采用的是最小二乘多项式拟合。为了评估和比较不同的数值微分技术,建议使用具有大量噪声的测量数据,并且计算导数的质量不仅要通过对图形显示的目视检查来评估,还要使用定量标准,如均方根误差。