Abstract

Postural control is a common mechanism to compensate for unexpected displacements of the body. In the older population, a slip or fall due to a failure of postural control is a common cause of morbidity and mortality. The ability of postural control decreases with aging or neuropathy. In this study, 2 groups, diabetics and non-diabetics in the older population, were compared to determine how patterns of postural sway during quiet standing were related to the detection of perturbation. The SLIP-FALLS system was applied to the measurement of sway and detection of perturbation. In phase 1 of the development of the predictive model, neural network algorithms were applied to find determinant variables for perturbation detection. In phase 2, a fuzzy logic inference system was developed to investigate the relationship between sway and perturbation detection. Results of this study may be applied to the design of floor mats or shoe insoles for preventing fatigue in workplaces.

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