Design optimization of modular mobility assistive devices via generative AI

Mobility assistive devices, such as ankle foot orthoses, prosthetic limbs, and knee braces, are essential for enhancing the mobility and quality of life of individuals with physical disabilities or injuries. However, developing these products involves a multi-criteria decision-making problem, as designers must address functional performance, durability, user comfort, and sustainability objectives. In this research, we propose a generative AI-driven framework that integrates circular economy principles into the design and optimization of polymer-based orthoses. This framework incorporates relevant technical, environmental, and economic factors at the early design phase to minimize waste, extend product use-life, and ensure adaptability to various user profiles. We then utilize large language models to facilitate automated design recommendations based on anthropometric data, product lifecycle assessments, and manufacturing constraints. The study demonstrates that merging generative AI with circularity metrics can yield innovative, user-centric solutions for optimizing the design of assistive devices.