Power considerations for the application of detrended fluctuation analysis in gait variability studies.

ABSTRACT: The assessment of gait variability using stochastic signal processing techniques such as detrended fluctuation analysis (DFA) has been shown to be a sensitive tool for evaluation of gait alterations due to aging and neuromuscular disease. However, previous studies have suggested that the application of DFA requires relatively long recordings (600 strides), which is difficult when working with clinical populations or older adults. In this paper we propose a model for predicting DFA variance in experimental data and conduct a Monte Carlo simulation to estimate the sample size and number of trials required to detect a change in DFA scaling exponent. We illustrate the model in a simulation to detect a difference of 0.1 (medium effect) between two groups of subjects when using short gait time s

SUBMITTER: Kuznetsov NA 

PROVIDER: S-EPMC5360325 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature