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Abstract The mechanical impedance of the joints of the leg governs the body's response to external disturbances, and its regulation is essential for the completion of tasks of daily life. However, it is still unclear how this quantity is regulated at the knee during dynamic tasks. In this work, we introduce a method to estimate the mechanical impedance of spring-mass systems using a torque-controllable exoskeleton with the intention of extending these methods to characterize the mechanical impedance of the human knee during locomotion. We characterize system bandwidth and intrinsic impedance and present a perturbation-based methodology to identify the mechanical impedance of known spring-mass systems. Our approach was able to obtain accurate estimates of stiffness and inertia, with errors under 3% and ∼13–16%, respectively. This work provides a qualitative and quantitative foundation that will enable accurate estimates of knee joint impedance during locomotion in future works.
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This content will become publicly available on April 1, 2026
Characterization of a Quasi-Direct Drive Knee Perturbation System for Mechanical Impedance Estimation
The mechanical impedance of the human lower-limb joints during locomotion encodes our understanding of how the neuromotor system regulates the behavior of these tasks. Impedance is also a key component of several strategies for translating this behavior to robots, powered prosthetic limbs, and people empowered by exoskeletons. However, due to difficulty in making accurate measurements, there is little empirical evidence for the impedance behaviors of joints other than the ankle during active walking tasks. In this letter we propose a measurement system based on a highly backdrivable quasi-direct-drive actuator and a carefully calibrated actuator torque model. Bench-top validation with known mechanical impedance human-substitutes, confirms the viability of this system as an impedance measurement tool. A pilot study with two subjects utilizing a custom knee-exoskeleton apparatus confirms the feasibility of this system for human walking experiments.
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- Award ID(s):
- 1846969
- PAR ID:
- 10627851
- Publisher / Repository:
- IEEE Robotics & Automation Letters
- Date Published:
- Journal Name:
- IEEE Robotics and Automation Letters
- Volume:
- 10
- Issue:
- 4
- ISSN:
- 2377-3774
- Page Range / eLocation ID:
- 3566 to 3573
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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