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

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.