3D-MFC: A method for computing critical gait parameters based on virtual marker tracking

Abstract

Minimum foot clearance (MFC) is defined as the minimum vertical distance between the lowest point of the swing foot or shoe and the walking surface in gait, which is now considered as a critical gait parameter for predicting trip-related fall risks. Different MFC methods have been used to assess fall risks by tripping, with the analytical method proposed by Begg et al. being the most widely used one. Since this method is based on assumption of a 2D triangular geometric model of the foot, the effects of out-of-plane rotations of the foot/shoe on MFC were not completely known. Furthermore, the accuracy of the MFC maybe influenced by factors such as shoe type, limiting its potential applications in clinical scenarios. Thus, this study proposes a novel method to calculate MFC parameter (called 3D-MFC) based on 3D modeling of the “virtual” markers of the shoe. By using a dynamic point-tracking technology, the 3D-MFC can automatically extract the MFC height while subject walking. From the Bland-Altman analysis, it was shown the 3D-MFC agreed well with that of the Begg's 2D-Geometric method. However, the mean absolute error (MSE) and root mean square error (RMSE) of the 3D-MFC method were less than 1 mm, which significantly outperformed the 2D-Geometric method, especially for subjects using rocker-bottom shoe. It is suggested that the 3D-MFC has potential to be an effective solution for identifying the MFC parameters and is expected to be used for biomechanical assessment of trip-related fall risks in the elderly.