CAREER: Task-Level Coordination of Motor and Machine for Fluent Lower-Limb Prostheses

University Of Notre Dame, Notre Dame IN

Investigators

Abstract

This Faculty Early Career Development (CAREER) grant will enhance the comfort and safety of lower-limb prostheses by studying the interplay between human motor control loops and device control designs. Current powered lower-extremity prostheses offer benefits over previous passive devices in terms of providing work when ascending stairs and contributing actively to balance. The interface between a user and their powered device, however, results in complex physical dynamics and motor adaptations that both shape and are shaped by the control strategy of the prosthesis. This project will address this interplay by using models of the fundamental mechanics of human gait to coordinate machine response in synergy with task-level motor control goals, and to understand how machine response affects human gait. This project will promote the progress of science by providing understanding into how human motor coordination is affected by assistive device operation. It has potential to advance national health and wellbeing by reducing falls for above-knee amputees through the restoration of lower limb function. The project supports education and broadening participation through (1) after-school STEM programs serving at-risk middle school students; (2) enhancement of graduate and undergraduate curricula; and (3) a new graduate student summer school for Robotics at the Mind, Machine, and Motor Nexus. This CAREER project will study the dynamic interplay between users and their prostheses through low-dimensional template models of locomotion, which are hypothesized to reflect the intrinsic neural control of movement. Experiments will provide extensive data on natural human gait, non-amputee gait using a prosthesis with a bypass adapter, and amputee gait with passive and active prostheses. These data will be used to identify task-level human motor coordination goals and to understand how they are affected by injury and by device operation. Computable frameworks will be investigated to rigorously disambiguate between candidate template models in a quantitative and data-driven fashion using a hybrid optimal control approach. In parallel, a new paradigm for the task-level control of prostheses will be established, and experiments will assess its effects on measures of balance, gait symmetry, and user comfort. The use of an NSF-sponsored open-source prosthetic leg will accelerate the diffusion of the project's methods, thereby hastening achievement of translational impacts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.