Identification and Correlation of Human Footfall Load Parameters Using Multivariate Analysis

Abstract

This research had two main objectives: to identify and quantify the multiple reaction parameters of human footfall load histories for 24 subjects; and to seek statistical correlations of the reaction parameters with two gaits: fitness walking and running, with two footfall surfaces: rigid and mat, and with two subject attributes: gender and arch index. These reaction parameters, measured with a force plate, include the subjects’ foot reaction forces in the three orthogonal directions and the particular features of these forces such as their duration, average values, peak values, and rates of loading. An automated data retrieval-software system evaluated these reaction parameters. The statistical correlations were made using principal component analysis (PCA), a method that projected the 13 identified footfall reaction parameters onto subsets of three or four parameters called principal components that contained most of the variance of the original thirteen. The results, among others, show couplings between the vertical and the peak medial load, but an uncoupling of the posterior–anterior loads with the loads in the other two directions.