FlexiScale: A Hybrid Marker-Based Scaling Method for Geometrically and Biomechanically Accurate Lower Limb Musculoskeletal Models

Subject-specific musculoskeletal (MSK) models with individualized anthropometric features are essential for accurate biomechanical analysis, given the considerable anatomical and mechanical variability across individuals. Marker-based scaling provides a noninvasive, efficient, and cost-effective strategy for personalizing generic MSK models, yet its reliability and accuracy remain insufficiently validated. This study proposes a hybrid scaling approach (FlexiScale), which combines segment-wise linear scaling with global nonlinear morphing based on radial basis function (RBF) interpolation. This method enables simultaneous adjustment of relative segment orientations and overall skeletal geometry. To comprehensively evaluate its performance, two simpler baseline models were also constructed, including a uniform linear scaling model and a segmental linear scaling model. A reliability analysis was conducted by comparing knee joint contact forces predicted by the three scaling models with in vivo measurements obtained from an instrumented knee prosthesis under identical gait conditions. Furthermore, an accuracy validation was performed by comparing joint contact forces and muscle forces predicted by each scaling model against those derived from medical image–based subject-specific models across three daily activities (level walking, stair ascent, and stair descent) in both male and female subjects. Compared to conventional linear methods, FlexiScale consistently produced the most accurate and reliable geometric and biomechanical predictions across tasks and subjects. These findings demonstrate that the proposed hybrid approach can generate geometrically and biomechanically more accurate and robust MSK models than conventional linear scaling methods, even without medical imaging, thereby supporting subject-specific assessments and large-scale applications in clinical and research settings.