Foot Deformity Determination and Health Risk Prediction Through Foot Plantar Analysis Using Pressure Sensor Matrix

Abstract

One of the most overlooked parts of the body is the feet. Foot health can generally affect the overall health of a person if not treated well. This study utilized Support Vector Machines and an artificial neural network to determine the foot deformity of a person by using a foot plantar pressure sensor matrix called Velostat. The researchers used raspberry pi to run the GUI programmed using Python. The developed device will determine if the feet are normal, high arched, or low arched. The testing was done on 40 respondents and resulted in 95% accuracy in determining foot deformity.