Typically impedance control parameters (e.g., stiffness and damping) in powered lower limb prostheses are fine-tuned by human experts (HMEs), which is time and resource intensive. Automated tuning procedures would make powered prostheses more practical for clinical use. In this study, we developed a novel cyber expert system (CES) that encoded HME tuning decisions as computer rules to auto-tune control parameters for a powered knee (passive ankle) prosthesis. The tuning performance of CES was preliminarily quantified on two able-bodied subjects and two transfemoral amputees. After CES and HME tuning, we observed normative prosthetic knee kinematics and improved or slightly improved gait symmetry and step width within each subject. Compared to HME, the CES tuning procedure required less time and no human intervention. Hence, using CES for auto-tuning prosthesis control was a sound concept, promising to enhance the practical value of powered prosthetic legs. However, the tuning goals of CES might not fully capture those of the HME. This was because we observed that HME tuning reduced trunk sway, while CES sometimes led to slightly increased trunk motion. Additional research is still needed to identify more appropriate tuning objectives for powered prosthetic legs to improve amputees' walking function.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.