The contribution of multibody optimization when using inertial measurement units to compute lower-body kinematics

Léonie Pacher; Nicolas Vignais; Christian Chatellier; Rodolphe Vauzelle; Laetitia Fradet

doi:10.1016/j.medengphy.2022.103927

The contribution of multibody optimization when using inertial measurement units to compute lower-body kinematics

Med Eng Phys. 2023 Jan:111:103927. doi: 10.1016/j.medengphy.2022.103927. Epub 2022 Dec 30.

Authors

Léonie Pacher¹, Nicolas Vignais², Christian Chatellier³, Rodolphe Vauzelle³, Laetitia Fradet⁴

Affiliations

¹ Equipe Robotique, Biomécanique, Sport, Santé, Institut PPRIME, UPR3346 CNRS Université de Poitiers ENSMA, Poitiers, 11, Boulevard Marie et Pierre Curie, Site du Futuroscope, F-86073 POITIERS CEDEX 9, France.
² Complexity, Innovation, Sports & Motor Activities (CIAMS) laboratory, Université Paris-Saclay, 91405 Orsay cedex, France.
³ Equipe SYstèmes et réseaux de COMmunications Optique et Radio, Institut XLIM UMR CNRS 7252, Poitiers, 11, Boulevard Marie et Pierre Curie, Site du Futuroscope, F-86073 POITIERS CEDEX 9, France.
⁴ Equipe Robotique, Biomécanique, Sport, Santé, Institut PPRIME, UPR3346 CNRS Université de Poitiers ENSMA, Poitiers, 11, Boulevard Marie et Pierre Curie, Site du Futuroscope, F-86073 POITIERS CEDEX 9, France. Electronic address: laetitia.fradet@univ-poitiers.fr.

PMID: 36792234
DOI: 10.1016/j.medengphy.2022.103927

Abstract

Kinematics obtained using Inertial Measurement Units (IMUs) still present significant differences when compared to those obtained using optoelectronic systems. Multibody Optimization (MBO) might diminish these differences by reducing soft-tissue artefacts - probably emphasized when using IMUs - as established for optoelectronic-based kinematics. To test this hypothesis, 15 subjects were equipped with 7 IMUs and 38 reflective markers tracked by 18 optoelectronic cameras. The subjects walked, ran, cycled on an ergocycle, and performed a task which induced joint movements in the transverse and frontal planes. In addition to lower-body kinematics computed using the optoelectronical system data, three IMU-based kinematics were computed: from IMU orientations without MBO; from MBO performed using the OpenSense add-on of the OpenSim software (OpenSim 4.2, Stanford, USA); as outputs from the commercialised MVN MBO (Xsens, Netherlands). Root Mean Square Errors (RMSE), coefficients of correlations, and differences in range of motion were calculated between the three IMU-based methods and the reference kinematics. MVN MBO seems to present a slight advantage over Direct kinematics or OpenSense MBO, since it presents 34 times out of 48 (12 degrees of freedom * 4 sports activities) a mean RMSE inferior to the Direct and OpenSense kinematics. However, it was not always significant and the differences rarely exceeded 2°. This study does not therefore conclude on a significant contribution of MBO in improving lower-body kinematics obtained using IMUs. This lack of results can partly be explained by the weakness of both the kinematic constraints applied to the kinematic chain and segment stiffening. Personalization of the kinematic chain, the use of more than one IMU by segment in order to provide information redundancy, or the use of other approaches based on the Kalman Filter might increase this MBO impact.

Keywords: Gait; Inertial measurement units; Lower-body kinematics; Multibody optimisation.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Artifacts
Biomechanical Phenomena
Humans
Movement*
Range of Motion, Articular
Walking*