Using 3D Scan to Determine Human Body Segment Mass in OpenSim Model

TL;DR

This paper evaluates the errors in human body segment mass estimation in OpenSim models using 3D scans, highlighting the impact on dynamic analysis accuracy and proposing improved estimation methods.

Contribution

It introduces a 3D scan-based method for more accurate segment mass estimation in OpenSim, reducing errors in biomechanical simulations.

Findings

Segment mass errors can reach 5.31% of body weight.

Errors cause up to 12.68% variation in joint moment calculations.

Using volume and density data offers an economical estimation alternative.

Abstract

Biomechanical motion simulation and dynamic analysis of human joint moments will provide insights into Musculoskeletal Disorders. As one of the mainstream simulation tools, OpenSim uses proportional scaling to specify model segment masses to the simulated subject, which may bring about errors. This study aims at estimating the errors caused by the specifying method used in OpenSim as well as the influence of these errors on dynamic analysis. A 3D scan is used to construct subject's 3D geometric model, according to which segment masses are determined. The determined segment masses data is taken as the yardstick to assess the errors of OpenSim scaled model. Then influence of these errors on the dynamic calculation is evaluated in the simulation of a motion in which the subject walks in an ordinary gait. Result shows that the mass error in one segment can be as large as 5.31\% of overall body weight. The mean influence on calculated joint moment varies from 0.68\% to 12.68\% in 18 joints. In conclusion, a careful specification of segment masses will increase the accuracy of the dynamic simulation. As far as estimating human segment masses, the use of segment volume and density data can be an economical choice apart from referring to population mass distribution data.