LAUSR

This study investigates the possibility of estimating body segment inertial parameters (BSIPs) and performing human dynamics analysis using embedded sensors. Affordable embedded inertial measurement units (IMUs) and instrumented force-sensing insoles have not yet demonstrated sufficient accuracy for dynamic assessments of motions in sports or rehabilitation tasks when compared with laboratory-grade solutions, such as marker-based stereophotogrammetric systems and force plates (FPs). In this article, we developed a BSIP identification pipeline to estimate inertial parameters among ten healthy young volunteers. Once these parameters are properly identified, several comparisons can be made. First, for the external wrench, we compare estimates derived from different kinematic modalities coupled with either identified BSIP or anthropometric tables against FP measurements. Second, for joint torques, we compare estimates using embedded kinematics and either identified BSIP or anthropometric tables to the best available reference, which comes from marker-based stereophotogrammetric systems combined with identified BSIP. For validation, in the Y-balance postural test, comparing external wrench estimates using kinematics from embedded IMUs and identified BSIP to FP measurements revealed a root mean square error (RMSE) of 5.9 N for forces and 18.0 N.m for moments, which corresponds to a large center of pressure position error of 3.2 cm. Overall, using identified BSIP reduced the normalized RMSE for joint torques by 6.5% compared with using anthropometric tables, suggesting that kinematic errors from embedded IMUs cannot be entirely compensated.