Date of Award

Spring 5-2015

Embargo Period


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Mechanical Engineering


Steven H. Collins


Recently-developed robotic prostheses have demonstrated that it is possible to design a prosthesis which makes it easier for unilateral transtibial amputees to walk. Unfortunately, it is unclear which design features are most important and which users will benefit most from these advanced technologies that increase prosthesis cost by an order of magnitude. I developed a novel experimental approach to resolving these design and prescription uncertainties. Candidate prosthetic feet are emulated during treadmill walking experiments using a high-performance o -board actuated and controlled lightweight robotic prosthesis. Prosthesis behavior is systematically varied while users' walking economy, performance, and satisfaction are measured. This process thereby determines unambiguous relationships between device behavior and outcomes of interest. In Chapter 1 of this thesis I motivate the approach. In Chapter 2 I detail the design and evaluation of the novel prosthesis emulator system. Then, in Chapter 3, I detail an experiment in which I test the simple walking model prediction that increasing prosthetic ankle push-o work will lessen leading limb collision, thereby reducing users' metabolic energy consumption. I demonstrate that increased push-o instead seems to primarily reduce energy consumption by aiding in the acceleration of the swing leg. In Chapter 4, I emulate the behavior of o -the-shelf prostheses, giving patients the opportunity to test-drive candidate devices prior to purchase, and enabling prescriptions to be justified by predictive experimental data. Finally, in Chapter 5, I demonstrate a human-in-the-loop prosthesis design optimization scheme that enables the manufacture of user-customized prostheses, which could ultimately supersede the need for prosthesis selection. vi vii This thesis lends insight into how powered ankle-foot prostheses can make walking easier and demonstrates that the degree to which individual users will benefit is highly dependent on their specific needs, expected walking conditions, and the choice of outcome measures. I hope that this work serves to improve mathematical models of human walking and contributes to a shift towards individualized prosthesis design and prescription.