Lower-limb amputees can suffer from preventable pain and bone disorders attributable to suboptimal prosthesis design. Predictive modelling and simulation of human walking using conventional biomechanical gait models offer an alternative to intuition-based prosthesis design, providing insight into the biomechanics underlying pathological gait. Musculoskeletal models additionally enable understanding of prosthesis contributions to the human musculoskeletal system, and both prosthesis and individual muscle contributions to body support and propulsion during gait. Based on this review, forward dynamic simulation of amputee musculoskeletal models have been used to perform prosthesis design optimization using optimal control and reflex-based control. Musculoskeletal model complexity and assumptions inhibit fully predictive musculoskeletal modelling in its current state, hindering computational prosthesis design optimization. Future recommendations include validating musculoskeletal models and resultant optimized prosthesis designs, developing less computationally-expensive predictive musculoskeletal modelling methods, and developing more efficient patient-specific musculoskeletal model generation methods to enable personalized prosthesis optimization.

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