SVM models in the diagnosis of balance impairments

Abstract

Trip-related falls is a major problem in the elderly population and research in the area has received much attention recently. The focus has been on devising ways of identifying individuals at risk of sustaining such falls. The main aim of this work is to explore the effectiveness of models based on Support Vector Machines (SVMs) for the automated recognition of gait patterns that exhibit falling behaviour. Minimum foot clearance (MFC) during continuous walking on a treadmill was recorded on 10 healthy elderly and 10 elderly with balance problems and with a history of tripping falls. MFC histogram characteristic features were used as inputs to the SVM model to develop relationships between M..