Antoine Muller

A comparative study of 3 body segment inertial parameters scaling rules

Inverse dynamics method consists in retrieving forces from motion capture data. It implies the use of a skeletal model that can be defined as a multibody articulated system. For each segment, body segment inertial parameters (BSIPs) have to be estimated. Without advanced techniques, BSIPs are estimated from anthropometric data. Many papers discussed the influence of the BSIP scaling on the inverse dynamics results (Pearsall & Costigan 1999; Rao et al. 2006; Reinbolt et al. 2007; Wesseling et al. 2014). These comparative studies were realized on gait analysis. However, further investigations remain necessary to extend these results, for example with other movements or for different populations. The aim of this paper was to present a benchmarking of three anthropometric BSIP scaling rules on overhead throwing motion.

Dealing with modularity of multibody models

In the current paper, we propose to adapt a descriptive method used in robotics to describe and simulate a skeletal model and make it modular. We also propose an illustration of the descriptive method by analyzing the elbow kinematics of an overhead throwing with two different forearm descriptions.

The MusIC method: a fast and quasi-optimal solution to the muscle forces estimation problem

Abstract The present paper aims at presenting a fast and quasi-optimal method of muscle forces estimation: the MusIC method. It consists in interpolating a first estimation in a database generated offline thanks to a classical optimization problem, and then correcting it to respect the motion dynamics. Three different cost functions – two polynomial criteria and a min/max criterion – were tested on a planar musculoskeletal model. The MusIC method provides a computation frequency approximately 10 times higher compared to a classical optimization problem with a relative mean error of 4% on cost function evaluation.