%0 Journal Article %1 Chau2004 %A Chau, Tom %A Parker, Kim %D 2004 %J IEEE Trans Biomed Eng %K Adult; Algorithms; Cerebral Palsy; Child; Computer Simulation; Diagnosis, Computer-Assisted; Gait; Gait Disorders, Neurologic; Humans; Locomotion; Models, Biological; Statistical; Periodicity; Physical Examination; Quality Control; Reproducibility of Results; Sensitivity and Specificity %N 2 %P 294--303 %T On the robustness of stride frequency estimation. %V 51 %X 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.

@article{Chau2004, abstract = {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.}, added-at = {2014-07-19T19:14:55.000+0200}, author = {Chau, Tom and Parker, Kim}, biburl = {https://www.bibsonomy.org/bibtex/22c2860063b3c2b4c2779b31b572e36d3/ar0berts}, groups = {public}, interhash = {8761722e5c5978610fa53c4f8a1f5343}, intrahash = {2c2860063b3c2b4c2779b31b572e36d3}, journal = {IEEE Trans Biomed Eng}, keywords = {Adult; Algorithms; Cerebral Palsy; Child; Computer Simulation; Diagnosis, Computer-Assisted; Gait; Gait Disorders, Neurologic; Humans; Locomotion; Models, Biological; Statistical; Periodicity; Physical Examination; Quality Control; Reproducibility of Results; Sensitivity and Specificity}, month = Feb, number = 2, pages = {294--303}, pmid = {14765702}, timestamp = {2014-07-19T19:14:55.000+0200}, title = {On the robustness of stride frequency estimation.}, username = {ar0berts}, volume = 51, year = 2004 }