Related Experiment Video
Updated: May 9, 2026
Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
Published on: April 11, 2018
Evaluation of graft stiffness and material nonlinearity on knee biomechanics after ACL reconstruction using a dynamic
Dangdang Wang1, Xijin Hua2, Zhongmin Jin3
1Tribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Background:
Artificial ACL graft design often emphasizes replicating native nonlinear behavior; however, the relative biomechanical contributions of graft stiffness and toe-region nonlinearity under functional loading remain unclear, limiting guidance for graft selection and tensioning.
Methods:
A dynamically validated lower-limb finite element-musculoskeletal model simulated walking, stair ascent, and stand-to-sit activities. The model incorporated anatomically detailed 3D representations of ligaments, cartilage, menisci, and patellofemoral contact, driven by motion capture data. Artificial ACL grafts with stiffness levels of 75, 125, 175, and 300 N/mm were evaluated using linear and nonlinear material formulations, isolating toe-region nonlinearity under low-strain conditions.
Results:
Graft stiffness showed a stronger influence on knee biomechanics than material nonlinearity. Increasing stiffness elevated ACL forces and induced measurable changes in tibial rotation and contact center translation, while its effect on global joint loading remained limited. Differences between linear and nonlinear models were detectable only during low-load phases and remained small. Grafts within 75-175 N/mm produced consistent joint responses, whereas higher stiffness (300 N/mm) increased ACL stress and kinematic deviations.
Conclusion:
Within this computational framework and functional activities, graft stiffness plays a more influential role than toe-region nonlinearity. When stiffness is controlled, the contribution of toe-region nonlinearity appears limited under low-strain conditions. These findings represent mechanistic insights from modeling and require further experimental and clinical validation.
