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The Prediction of Knee Contact Forces with the Novel Two-Dimensional Dynamic Model of Human Knee Cover

The Prediction of Knee Contact Forces with the Novel Two-Dimensional Dynamic Model of Human Knee

Open Access
|Jul 2026

Abstract

This study presents a computationally efficient two-dimensional dynamic model of the human knee for simulating tibiofemoral contact mechanics during gait. To address the limitations of existing musculoskeletal frameworks in modeling deformable cartilage contact, a customized dynamic contact formulation was integrated with an OpenSim-based musculoskeletal pipeline. Experimental motion capture data—including joint kinematics and ground reaction forces—were used to drive the model and estimate tibiofemoral contact forces and cartilage indentation. The modeling framework incorporates anatomically derived geometric profiles of the femoral and tibial contact surfaces, a generalized collision detection algorithm, and a nonlinear viscoelastic contact law representing layered cartilage–bone interaction. Computational efficiency was achieved through optimized collision detection and reduced data-handling latency, enabling subject-specific simulations. The model’s performance was evaluated using gait data from healthy and osteoarthritic knee geometries. Simulation results demonstrated maximum cartilage penetration depths of 0.795 mm for the healthy knee and 0.521 mm for the osteoarthritic knee, representing 0.5 mm cartilage-on-cartilage and 0.021 mm bone-on-bone interaction. These values fall within reported in-vivo physiological deformation ranges. The proposed framework provides a robust and efficient tool for predicting knee joint contact behavior, with potential applications in assistive device design, rehabilitation, and computational biomechanics.

DOI: https://doi.org/10.65731/ama-2026-0012 | Journal eISSN: 2300-5319 | Journal ISSN: 1898-4088
Language: English
Page range: 111 - 120
Submitted on: May 19, 2025
Accepted on: Dec 3, 2025
Published on: Jul 16, 2026
In partnership with: Paradigm Publishing Services

© 2026 Amirhosein Javanfar, Mohammadreza Azimi, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.