Walking is just putting one foot in front of the other, but there are complex biomechanical factors taking place throughout each step — especially in the ankle.

Hyunglae Lee, an assistant professor of mechanical and aerospace engineering in the Ira A. Fulton Schools of Engineering at Arizona State University, took a unique approach to researching the ankle’s dynamic movement during walking. Arizona State University Assistant Professor Hyunglae Lee (right) combines expertise in robot-aided neurorehabilitation and neuromuscular control of human ankles, shoulders and other joints to develop innovative platforms for understanding and aiding human health. Photo by Erika Gronek/ASU Download Full Image

The results of this work — developed in collaboration with Elliott Rouse, an assistant professor of mechanical engineering at the University of Michigan, Ann Arbor, and Hermano Igo Krebs, a principal research scientist at Massachusetts Institute of Technology, and originally published in 2016 in the IEEE Journal of Translational Engineering in Health and Medicine — is helping improve rehabilitation and human-robot interaction applications.

“Outcomes of this and related studies will not only contribute to the scientific advancement of our understanding of normal and pathological ankle behavior during various real-life task conditions, but also the development of assistive or rehabilitation devices capable of providing optimal support without hindering natural lower extremity function,” said Lee, who has built upon this research over the past several years.

As the second-highest cited work over the past five years in the IEEE Journal of Translational Engineering in Health and Medicine, this year Lee’s 2016 paper earned the second prize in the IEEE Engineering Medicine and Biology Society Prize Paper Awards.

Analyzing ankles

The technique of walking, or gait, is made up of two main parts. The stance phase involves the foot that stays on the ground while the swing phase involves the other leg that swings forward to take the next step.

Ankle joint impedance — the relationship between the joint position and the force of rotation in motion — is a fundamental part of the human neuromuscular system that explains the energy exchanges that occur while walking.

“Quantification of this property is critical in understanding the stability of the human body as well as the quality of walking function,” Lee said. “Until we published this work, almost all previously reported work on the quantification of ankle impedance was strictly limited to static posture conditions, such as seated and quiet standing positions, and there was no systemic way to quantify ankle impedance during dynamic walking.”

In those studies, researchers used motion analysis, 3D motion capture and force-plate sensing systems to comprehensively understand ankle biomechanics, but these methods don’t allow for the study of impedance. So, Lee and his collaborators developed a different approach.

Their system, described in the award-winning 2016 paper, involved two robotic platforms: one recessed into the ground on which a research subject could walk, and another that is worn on the ankle and introduces perturbations to the ankle throughout the stance and swing phases of walking.

Then the team used system identification to quantify ankle impedance through the analysis of input perturbations and the corresponding output responses.

“This integrated approach allowed us to reliably characterize ankle impedance throughout the full gait cycle during walking, which is not achievable in the traditional motion analysis settings,” Lee said.

When compared to static poster studies, the reliability of Lee and his collaborators’ method was just as effective and reliable in quantifying impedance. They also found that ankle impedance could be approximated accurately through three components: the stiffness of the ankle joint, the ability to absorb perturbations (damping) and the tendency to remain in motion or at rest (inertia). The data showed ankle stiffness underwent the most adjustments during the gait cycle.

“Joint stiffness is one of the main focuses in controlling human-interactive robots and administering neurorehabilitation for functional improvement,” Lee said.​