Pattern Recognition for Identification of Gender of Individuals from Ground Reaction Force Parameters

Abstract

The present study uses a neural network pattern recognition tool to determine its efficacy in identifying the gender of individual participants. For this purpose, the ground reaction force patterns of 33 individuals (comprising healthy male as well as female participants) were recorded over the course of 132 trials. The peak and trough parameters were established for each pattern and used as inputs for the algorithm. These data clusters were used to train, test and validate the neural network using a pattern recognition tool. The results of this work show that this network presents capability of identifying the gender of participants from the peak ground reaction force parameters.