Predictive Gait Simulations of Human Energy Optimization

Koelewijn A, Selinger JC (2022)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2022

Publisher: Springer Science and Business Media Deutschland GmbH

Edited Volumes: Wearable Robotics: Challenges and Trends

Series: Biosystems and Biorobotics

City/Town: Cham

Book Volume: 27

Pages Range: 377-381

ISBN: 978-3-030-69547-7

DOI: 10.1007/978-3-030-69547-7_61

Abstract

We previously demonstrated that humans can continuously adapt their gait to optimize energetic cost in real-time when wearing a lower-limb exoskeleton. Here, we aim to recreate this paradigm using predictive gait simulations to further investigate how the nervous system performs this optimization and how energy costs change locally. To match the real-world experiment, we modeled a knee-worn exoskeleton that applied resistive torques that were either proportional or inversely proportional to step frequency—decreasing or increasing the energy optimal step frequency, respectively. We solved simulations with and without the knee exoskeleton and with fixed and free step frequency. We were able to replicate the experiment, finding higher and lower optimal step frequencies than in the natural walking under each respective condition. Our simulated resistive torques and optimized objective function resembled the measured experimental resistive torque and metabolic energy landscape. Muscle metabolic power changed for individual muscles spanning all three joints and revealed distinct coordination strategies consistent with each exoskeleton controller condition.

Authors with CRIS profile

Anne Koelewijn Juniorprofessur für Computational Movement Science (Stiftungsprofessur)

Involved external institutions

Queen's University CA Canada (CA)

How to cite

APA:

Koelewijn, A., & Selinger, J.C. (2022). Predictive Gait Simulations of Human Energy Optimization. In Juan C. Moreno, Jawad Masood, Urs Schneider, Christophe Maufroy, Jose L. Pons (Eds.), Wearable Robotics: Challenges and Trends. (pp. 377-381). Cham: Springer Science and Business Media Deutschland GmbH.

MLA:

Koelewijn, Anne, and Jessica C. Selinger. "Predictive Gait Simulations of Human Energy Optimization." Wearable Robotics: Challenges and Trends. Ed. Juan C. Moreno, Jawad Masood, Urs Schneider, Christophe Maufroy, Jose L. Pons, Cham: Springer Science and Business Media Deutschland GmbH, 2022. 377-381.

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