Development of a Framework for the Biomechanical Analysis of the Diabetic Foot Integrating Multisegmental Foot Movement Analysis Data, EMG-driven Musculoskeletal Modeling, and Finite Element Analysis.

The diabetic foot is one of the most disabling complications of diabetes mellitus: peripheral neuropathy and the resulting structural alterations predispose patients to plantar ulceration. Baropodometry, the clinical standard for risk assessment, measures foot–ground interface pressure and is at best a moderate predictor of ulceration, since it cannot capture the internal soft-tissue stress where mechanical failure is believed to originate. This thesis develops and validates an integrated computational framework to estimate that internal stress from experimental gait data, coupling multisegmental foot motion analysis, electromyography (EMG)-informed musculoskeletal (MSK) modeling, and finite element (FE) analysis. Gait data (marker trajectories, ground reaction forces, plantar pressure, and surface EMG) were acquired on a retrospective cohort of five subjects: one control, two diabetic without neuropathy, and two with neuropathy. A subject-scaled multisegment OpenSim model of the right lower limb estimated muscle forces through an EMG-informed optimal control problem (OpenSim Moco) and a static-optimization baseline. The resulting forces and kinematics served as boundary conditions for group-generic FE models of the foot–ankle complex, scaled to each subject, with hyperelastic plantar soft tissue including diabetes-specific stiffening. Quasi-static simulations at four gait instants were validated against measured plantar pressure. The EMG-informed branch converged more reliably than static optimization (97.5% versus 62.5% of simulations) and reproduced plausible ankle co-contraction, but where both converged it did not significantly improve plantar pressure prediction, an outcome attributed mainly to the generic FE geometry. Accuracy was highest in the forefoot, the region most affected by neuropathic ulceration, supporting the framework's potential, once extended with subject-specific imaging and broader muscle instrumentation, for assessing internal tissue loading in ulceration risk.