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In a study performed at Utah State University, participants were prompted to evaluate the stability of pictured human postures while standing on a force plate. The force plate was used to collect the center of pressure of the subjects by recording measurements in the vertical and horizontal directions. The way these factors fluctuate over time and the irregularity in this fluctuation, specifically, can give insight into the subject’s postural stability. Rather than working with summary statistics such as means and variances of fitting parameters of a distribution as commonly done in statistics, we want to measure irregularity through analyzing the presence of patterns, or lack thereof, in the sequential center of pressure values. To measure such recurrent patterns, approximate entropy (ApEn), a time series statistic, was developed in the field of biomedical data analysis. There is compelling research that ApEn is a reliable statistic in measuring human stability. For instance, approximate entropy has been shown to be a more reliable measure of recovery time in concussed athletes and sitting ability in infants with cerebral palsy. We apply approximate entropy, along with time series and visualization techniques, to analyze the previously mentioned force plate data. Similar to the score in a horror film causing physical reactions such as sweaty palms or goosebumps, the external factor of viewing more or less stable postures could affect the subjects’ individual stability. This relationship could have implications for modeling the progression of motor skills, understanding human development, and the design of environments for rehabilitation.

Publication Date



Logan, UT


approximate entropy, human movement, posture


Mathematics | Statistics and Probability

Measuring Irregularity Via Approximate Entropy: How Does Perceived Human Instability Affect One's Own Stability?