A DATA-MINING BASED METHOD FOR THE GAIT PATTERN ANALYSIS

Abstract

The paper presents a method developed for the gait classification based on the analysis of the trajectory of the pressure centres (CoP) extracted from the contact points of the feet with the ground during walking. The data acquirement is performed ba means of a walkway with embedded tactile sensors. The proposed method includes capturing procedures, standardization of data, creation of an organized repository (data warehouse), and development of a process mining. A graphical analysis is applied to looking at the footprint signature patterns. The aim is to obtain a visual interpretation of the grouping by situating it into the normal walking patterns or deviations associated with an individual way of walking. The method consists of data classification automation which divides them into healthy and non-healthy subjects in order to assist in rehabilitation treatments for the people with related mobility problems