Title
Identification of Time-Varying Ankle Joint Impedance During Periodic Torque Experiments Using Kernel-Based Regression
Author
Cavallo, Gaia (Vrije Universiteit Brussel)
Cop, Christopher P. (University of Twente)
Sartori, M. (University of Twente)
Schouten, A.C. (TU Delft Biomechatronics & Human-Machine Control; University of Twente) 
Lataire, John (Vrije Universiteit Brussel)
Contributor
Torricelli, Diego (editor)
Akay, Metin (editor)
Pons, Jose L. (editor)
Date
2022
Abstract
Joint impedance is a common way of representing human joint dynamics. Since ankle joint impedance varies within the gait cycle, time-varying system identification techniques can be used to estimate it. Commonly, time-varying system identification techniques assume repeatably of joint impedance over cyclic motions, without taking into consideration the inherent variability of human behavior. In this paper, a method that assumes smooth, cyclic joint impedance, yet allows for cycle-to-cycle variability, is proposed. The method was tested on isometric, cyclic experimental data from the ankle under conditions with a time variation comparable to the expected one during the gait cycle. The estimated model could describe the data with high accuracy (VAF of 94.96%) and retrieve realistic inertia, damping and stiffness parameters. The results provide motivation to further apply the method on experiments under dynamic conditions and to employ the proposed method as a tool for investigating the human joint dynamics during cyclic movements.
To reference this document use:
http://resolver.tudelft.nl/uuid:20f2a196-471f-4139-81f0-ec9fd7f30186
DOI
https://doi.org/10.1007/978-3-030-70316-5_79
Publisher
Springer
Embargo date
2022-04-02
ISBN
978-3-030-70315-8
Source
Converging Clinical and Engineering Research on Neurorehabilitation IV: Proceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13–16, 2020
Event
ICNR 2020: International Conference on NeuroRehabilitation (Virtual), 2020-10-13 → 2020-10-16
Series
Biosystems and Biorobotics, 2195-3562, 28
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
book chapter
Rights
© 2022 Gaia Cavallo, Christopher P. Cop, M. Sartori, A.C. Schouten, John Lataire