Personalized musculoskeletal models of the human trunk are essential for advancements in diagnosis, medical devices development, and ergonomics. In a previous study, a finite element model (FEM) of the human trunk was developed, and its effective mechanical properties such as stiffness and damping were calibrated using experimental data from a single participant when subjected to time-dependent excitations at the thoracic level. The objective of the present work is to extend this modeling approach by evaluating its ability to incorporate inter-individual variability. To this end, an identical experimental campaign was conducted on a second participant. The model parameters were then identified for this new subject using the same calibration methodology. A strong correlation was obtained between the simulated results and the experimental data from the second participant. This successful outcome confirms the model adaptability to other individual variation. The validated approach constitutes a reliable tool for generating realistic and subject-specific databases intended for advanced applications in machine learning and biomechanical simulation.
Moalla et al. (Fri,) studied this question.