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Journal of The Royal Society Interface· 2026Q1

OpenGRF: prediction of ground reaction forces and moments during activities of daily living using OpenSim

Andrea Di Pietro, Francesca Di Puccio, Luca Modenese

Short summary

OpenGRF, a new OpenSim tool, estimates ground reaction forces and moments (GRF&Ms) and center of pressure (CoP) directly from kinematic data, showing high accuracy for vertical GRFs (nRMSE ≤1.5%) and ankle moments (nRMSE ≈1.7%).

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Key points

  • OpenGRF estimates ground reaction forces/moments (GRF&Ms) and center of pressure (CoP) from kinematics using OpenSim.
  • Vertical GRF predictions achieved nRMSE ≤1.5% and ρ ≥0.94.
  • Ankle moments were predicted with high fidelity (nRMSE ≈1.7%, ρ ≈0.98).
  • Medio-lateral GRF and free moment predictions were less reliable, especially during stair tasks.

AI-generated from the title and abstract; the full text is not read.

Abstract

Abstract 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 (ρ), CoP error, and Statistical Parametric Mapping (SPM) Results Results showed high accuracy for vertical GRF (nRMSE ≤1.5%, ρ ≥0.94), particularly during level walking, and good accuracy for anterior–posterior GRF (nRMSE 4.4–6.1%, ρ = 0.81–0.91). Medio–lateral GRF was less reliable, especially in stair tasks (nRMSE up to 11.2%, ρ 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 ≈1.7%, ρ ≈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.

The authors' abstract, as published at the source. Journal of The Royal Society Interface, 2026 · DOI ↗

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Field: Biomedical Engineering

Biomedical EngineeringEngineering