Application of feedforward backpropagation neural network to center of mass estimation for use in a clinical environment

Abstract

In this paper, a feedforward backpropagation neural network model is developed to estimate the resultant center of mass (COM) trajectory in the sagittal plane. The COM trajectory is one of the primary outputs of the human postural control system, and is indicative of the system's stability. However, currently available systems that calculate the COM are not clinically available, making it difficult to widely assess balance problems. The inputs to the neural network model developed in this paper are obtained using equipment that is inexpensive, easy to use and portable. The results indicate that neural network models show promising results for obtaining COM estimates that have clinical applications.