Abstract
Inverse dynamics problems are usually solved in the analysis of human gait to obtain reaction forces and moments at the joints. However, these actions are not the actual forces and moments supported by the joint structure, because they do not consider the forces of the muscles acting across the joint. Therefore, to analyse bone-on bone forces it is necessary to estimate those muscle forces. Usually, this problem is addressed by means of optimization algorithms. One of the parameters required to solve this problem is the musculotendon geometry. These data are usually taken from cadavers or MRI data from several subjects, different from the analysed subject. Then, the model is scaled to the subject morphology. This procedure constitutes a source of error. The goals of this work were two. First, to perform a sensitivity analysis of the influence of muscle insertion locations on the muscle forces acting on the hip joint and on the hip joint bone-on-bone forces. Second, to compare the hip joint bone-on-bone forces during gait cycle obtained through muscle insertion locations taken from a musculoskeletal model template and a scaling procedure to those obtained from a subject-specific model using an MRI of the subject. The problem was solved using OpenSim. Results showed that anatomical variability should be analysed from two perspectives. One the one hand, throughout the gait cycle, in a global way. On the other hand, at a characteristic instant of the gait cycle. Variations of ±1 cm in the position of the attachment points of certain muscles caused variations of up to 14.21% in averaged deviation of the muscle forces and 58.96% in the peak force in the modified muscle and variations up to 57.23% in the averaged deviation of the muscle force and up to 117.23% in the peak force in the rest of muscles. Then, the influence of that variability on muscle activity patterns and hip bone-on-bone forces could be described more precisely. A biomechanical analysis of a subject-specific musculoskeletal model was carried out. Using MRI data, variations up to 5 cm in the location of the insertion points were introduced. These modifications showed significant differences between the baseline model and the customized model: within the range [-12%, 10%] for muscle forces and around 35% of body weight for hip bone-on-bone forces.
Highlights
IntroductionTwo of the most interesting aspects are the estimation of muscle forces carried out during movement and loads supported by joints, the so-called bone-on-bone forces
Movement analysis techniques are useful tools to study human locomotion
Two of the most interesting aspects are the estimation of muscle forces carried out during movement and loads supported by joints, the so-called bone-on-bone forces
Summary
Two of the most interesting aspects are the estimation of muscle forces carried out during movement and loads supported by joints, the so-called bone-on-bone forces. The latter is a widely studied problem in Biomechanics but continues being a topic of interest due to the importance of a correct estimation of the loads applied to the joints in clinical studies or in sport sciences [1,2,3,4,5,6,7,8], among others. One of the most usual approaches employed in the estimation of bone-on-bone forces is solving an inverse dynamics problem [9,10,11] The solution of this problem yields joint forces and moments that balance the external forces: gravitational, inertial or externally applied forces. This problem is addressed by means of optimization algorithms [12,13]
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