Chau Tom, Parker Kim
Department of Rehabilitation Engineering, Bloorview MacMillan Children's Centre, 350 Rumsey Road, Toronto, ON M4G 1R8, Canada.
IEEE Trans Biomed Eng. 2004 Feb;51(2):294-303. doi: 10.1109/TBME.2003.820396.
The robustness of stride frequency estimation (location and spread) from stride period data is investigated using influence functions. Theoretical analysis reveals that stride frequency estimates by Stokes et al. and by direct calculation have unbounded influence functions and zero breakdown points, implying a lack of both local and global robustness. Comparison of estimates obtained from an ensemble of pathological gait stride time series shows that on average, differences among estimators are not statistically significant (p > or = 0.59) for long time series (hundreds of strides). Specific circumstances under which nonrobust estimates depart from robust estimates are investigated in terms of outlier influence. We recommend some heuristic rules-of-thumb for prudent selection of nonrobust stride frequency estimators for a given stride time series. The theoretical and empirical estimator comparisons suggest that in general, more research on estimator robustness in quantitative gait analysis is warranted.
利用影响函数研究了从步幅周期数据估计步频（位置和离散度）的稳健性。理论分析表明，斯托克斯等人的步频估计方法以及直接计算法具有无界影响函数和零崩溃点，这意味着缺乏局部和全局稳健性。对从一组病理性步态步幅时间序列获得的估计值进行比较表明，对于长时间序列（数百步），估计器之间的差异平均而言在统计学上不显著（p≥0.59）。根据异常值影响研究了非稳健估计值与稳健估计值不同的具体情况。我们推荐一些启发式经验法则，以便为给定的步幅时间序列谨慎选择非稳健步频估计器。理论和实证估计器比较表明，总体而言，在定量步态分析中对估计器稳健性进行更多研究是有必要的。
