EVALUATION AND PREDICTION OF HUMAN GAIT PARAMETERS USING UNIVARIATE, MULTIVARIATE AND STEPWISE STATISTICAL METHODS

Abstract

This research was carried out to establish the relationship between human anthropometric data and corresponding gait variables. A group comprising 35 participants (18 male and 17 female) was selected for the current study. The study consisted of trials in which each participant was asked to walk the length of the instrumented walkway (Kistler’s force platform inset) at a self-selected speed. Using a four-camera motion analysis system, the kinematic and kinetic parameters of each trial were calculated. The peak values obtained from the data curves were used to generate the necessary regression fits. In order to establish the correlation between the anthropometric data of human and the gait parameters, the univariate, multivariate and stepwise fits were generated. Further, the statistical methods were employed to evaluate the [Formula: see text], [Formula: see text] and [Formula: see text]-values for each fit. The current multivariate study indicates an increasing trend in [Formula: see text] values and decreasing trend for [Formula: see text]-values when compared with the univariate fits and the results follow the expected line.