Melissa Taylor



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Biological variability is critical for healthy function and is present in all types of physiological movements. Variability exists on a spectrum in which the optimal amount falls between two extremes: a lack of variability indicating rigidity and limited adaptability and excessive variability indicating instability and random, uncontrolled motion. It is believed that nonlinear analyses provide insight into variability that can help predict future movements based on current movements. Detrended fluctuation analysis (DFA) is a widely used nonlinear analysis tool for postural control research. A limitation of DFA is that the results are heavily dependent on input parameters (data length, window size, and scaling region) used to determine the scaling exponent α; however, the input parameters are selected by the researcher and little published guidance exists to aid in their selection. The aim of this research is to examine the effects of changing input parameters on DFA of postural control data and to determine best practices for their selection in order to improve the consistency of the analysis and ensure that important effects in postural control data are not lost or skewed. MATLAB will be used to create theoretical chaotic and white noise time series with random initial conditions and known α values, and center of pressure sway measures will be taken for healthy adults using a balance plate. The theoretical and experimental data will be subjected to DFA where data length, window size, and scaling region will be varied independently. The value of α will be determined for all combinations of input parameters and the effects of varying these parameters will be explored. Statistical significance (p<0.05) of any of the main effects or interactions will indicate the extent to which α is dependent on the input parameters, allowing suggested guidelines for future researchers to be determined.

Publication Date


Project Designation

Graduate Research

Primary Advisor

Kimberly Bigelow

Primary Advisor's Department

Mechanical Engineering


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The Effect of Input Parameters on Detrended Fluctuation Analysis of Postural Control Data