OpenGRF: Predicting Ground Reaction Forces and Moments During Daily Living Activities in OpenSim

Background and Objectives Ground reaction forces and moments (GRF&Ms), typically measured using force plates, are key inputs for musculoskeletal simulations. OpenSim currently lacks a tool to predict GRF&Ms directly from kinematics. This study presents OpenGRF, an OpenSim−based tool designed to estimate GRF&Ms and the centre of pressure (CoP) from joint kinematic data and validates its performance against force plate recordings. Methods The proposed methodology integrates calibrated foot−ground contact probes with an optimization framework based on computed muscle control, while CoP is computed accounting for both kinematic and dynamic contributions. For validation, a scaled FullBodyModel (37−DoF without muscles) was created for seven healthy adults performing six trials each of level walking, stair ascent, and stair descent, for a total of 126 marker-based trials. GRF&Ms predictions were compared to reference force plate data using normalized RMSE (nRMSE), Pearson correlation coefficients (p), CoP error, and Statistical Parametric Mapping (SPM). Results Results showed high accuracy for vertical GRF (nRMSE up to 1.5%, p higher than 0.94), particularly during level walking, and good accuracy for anterior−posterior GRF (nRMSE 4.4−6.1%, p = 0.81−0.91). Medio−lateral GRF was less reliable, especially in stair tasks (nRMSE up to 11.2%, p down to 0.48). Free moments were the most challenging quantity to predict across all tasks (nRMSE up to 28%). In contrast, ankle moments were predicted with high fidelity (nRMSE almost 1.7%, p almost 0.98). Median CoP errors were 21−23 mm, with largest discrepancies during double support. Conclusions OpenGRF enables physics-consistent estimation of GRF&Ms and CoP directly from kinematics, achieving the highest accuracy for vertical GRFs and predicting ankle moments that closely match those obtained from force plate measurements.