NRI: Simulation Guided Design To Optimize the Performance of Robotic Lower Limb Prostheses

University Of Massachusetts Amherst, Amherst MA

Investigators

Abstract

The goal of this project is to use sophisticated computer models of the human body to help design the next generation of robotic prosthetic technologies that maximize mobility for lower-limb amputees. The major outcome of this project will be an improved approach for designing prosthetic devices that reduce loading on the body and make walking easier. The success of this project will improve the quality of life for lower limb amputees by increasing their mobility and their ability to participate in the activities of daily life. The proposed research is especially relevant for older amputees whose residual limbs cannot tolerate significant loading. This award will also support the training of the next generation of engineers and scientists and the development of an innovative STEM robotics program targeted toward middle and high school teachers and their students. This project is focused on creating a new design process for assistive robotic devices that aid people with mobility impairments. Using modeling and simulation, optimal robot forms and controls will be identified. The case study for this project is the development of prostheses for below-knee amputees. The guiding principle of the project is to consider the complete and altered anatomy of the person and develop solutions that are not limited to anthropomorphic mimicry. Detailed musculoskeletal models and optimal control simulations will be used to guide the robotic prosthesis development process towards optimized loading conditions while minimizing metabolic energy consumption. In this process, the optimal prosthesis form and specifications are initially unknown and are generated through predictive simulations. The results will then be reverse-engineered to develop robotic ankle prostheses that enable these optimal gait patterns for below-knee amputees. This approach will later be extended to maximize the performance of other co-robot systems such as exoskeletons and other rehabilitation robots.