A method for body posture classification of three-dimensional body models in the sagittal plane

Abstract

The main purpose of this research was to develop a method for the classification of body posture types, using a three-dimensional body scanner and data on anthropometric measurement. A sample of 102 male test subjects, aged from 20 to 30 years, and without structural deformities of the locomotor system, were scanned. Anthropometric body measurement was performed and 16 measurements were selected to calculate upper and lower body curve angles as a set of posture indicators. The number of maximally different groups of test subjects was determined using k-means cluster analysis and factor analysis of established posture indicators. The sampling into three upper and three lower posture types showed the largest statistically significant differentiation, comparing the results of variance analysis between and within the obtained groups, which confirmed three main components extracted by factor analysis. Discriminant analysis used in order to determine differences between posture types showed which indicators are the most important when classifying test subjects belonging to a particular upper or lower posture type. Classification functions were defined based on discrimination functions and their factor loadings, and used to calculate a matrix of correctly classified test subjects. The classification matrix showed very high prediction possibility of established posture indicators and the proposed method for body posture classification.