Estimation of Joint Kinetics During Manual Material Handling Using Inertial Motion Capture: A Follow-Up Study - Skals, Sebastian; de Zee, Mark; Skipper Andersen, Michael (Journal of biomechanical engineering, 2025)
Musculoskeletal models based on inertial motion capture (IMC) and ground reaction force (GRF) prediction hold great potential for field-based risk assessment of manual material handling (MMH). However, previous evaluations have identified inaccuracies in the methodology's estimation of spinal forces, while the accuracy of other key outcome variables is currently unclear. This study evaluated knee, shoulder, and L5-S1 joint reaction forces (JRFs) derived from a musculoskeletal model based on inertial motion capture and GRF prediction against a model based on simultaneously collected optical motion capture (OMC) and force plate measurements. Data from 19 healthy subjects performing lifts with various horizontal locations (HLs), deposit heights (DHs), and asymmetry angles (AAs) were analyzed, and the consistency and absolute agreement of the model estimates statistically compared. Despite varying levels of agreement across tasks and variables, considerable absolute differences were identified for the L5-S1 axial compression (AC) (root-mean-square error (RMSE) = 63.0-94.2%BW) and anteroposterior (AP) shear forces (RMSE = 40.9-80.6%BW) as well as the bilateral knee JRFs (RMSE = 78.9-117%BW). Glenohumeral JRFs and vertical GRFs exhibited the highest overall consistency (r = 0.33-0.91, median 0.78) and absolute agreement (RMSE = 7.63-34.9%BW), while the L5-S1 axial compression forces also showed decent consistency (r = 0.04-0.89, median 0.80). The findings generally align with prior evaluations, indicating persistent challenges with the accuracy of key outcome variables. While the modeling framework shows promise, further development of the methodology is encouraged to enhance its applicability in ergonomic evaluations.