Application of a More Advanced Procedure in Defining Morphological Types

Abstract

It is well known that the most evident differences in humans are those related to anthropometric characteristics, and that during continuous monitoring the relation between human behavior and human abilities concerning their anthropometric characteristics was observed. The aim of this study was to detect and define the morphological types with the use of slightly different and more advanced methodologies. The sample included 149 male subjects, first-year students of the Faculty of Sport and Physical Education in Novi Sad, using an anthropometric measurement technique. A total of 12 anthropometric measures, defined according to the fourdimensional morphological model was used. For all variables, basic descriptive statistics were calculated while student grouping was performed using taxonomic neural network - Intruder. Initial taxonomic classification of artificial entities by neural network Intruder accepted four clusters: endomorph or pyknic, ectomorph or leptosomic, astenomorph and gracile type. The results indicate that the identification and definition of morphological types with the use of a slightly different and more advanced procedure leads to better and earlier perception of certain characteristics which are necessary, both for the selection of specific sports, and in the prevention of various diseases and abnormalities in behavior and functioning.