Fast tool to evaluate 3D movements of the foot-ankle complex using multi-view depth sensors

Abstract

Movement disorders of the human foot-ankle complex are a common occurrence, owing to the altered joint mechanics during foot-ground interactions. Diagnostics of such movement disorders will require quantitative tools to evaluate in-vivo foot motions, in particular to the multi-segment/joint foot kinematics (MSFK), during gait. Unfortunately, current MSFK analysis largely rely on conventional technologies, such as skin-marker based motion capturing, video fluoroscopy and dynamic 3D scanning, being extremely time-consuming and costly. In this work, a novel movement tracking method, named the point-cloud foot analysis (PFA), was implemented with multi-view depth sensors, to allow fast evaluations of 3D motions of the foot-ankle complex during gait. Quantitative analysis obtained by the PFA methods and their accuracy relative to the conventional MSFK analysis methods were evaluated. The 3D surface reconstructions of the foot-ankle complex were achieved with a RMSE less than 2 ​mm. It was proven to be feasible to track multi-segment foot motions in both healthy and diseased subjects during walking conditions, with the processing time decreased from more than 4–6 ​h to less than 6 ​min for the entire flow of the contact phase analysis. The PFA method can be useful for fast evaluations of the movement disorders of the foot-ankle complex in diagnostics and design of therapeutic interventions and rehabilitation programs for clinical applications.

Keywords

• Biomechanics
• Foot model
• Joint mechanics
• Movement disorders
• Depth sensor