Footstep Classification Methodology using Piezoelectric Sensors Embedded in Insole

Abstract

This article presents a proposal for a methodology to classify the types of steps, using piezoelectric sensors embedded in an ethylene-vinyl acetate (EVA) insole, configuring a low-cost intelligent insole. From a few steps or a walk by the user, the electrical signals generated by the piezoelectric sensors are measured or stored for later treatment and analysis. The steps of the proposed methodology were applied step by step in tests carried out to classify the types of footsteps of male and female users, who used the intelligent insoles built into running shoes. The proposed methodology was also implemented in a computational code that was applied to classify the types of steps in the performed tests. The step classification results were satisfactory, compared with the specialized literature. It should be noted that the classification obtained from the application of the methodology is a suggestion of the type of footfall from an engineering point of view, and the result should be evaluated by a specialized health professional.