Model-based estimation of ankle joint stiffness during dynamic tasks

A validation-based approach

Conference paper (2019)

Authors

Christopher P. Cop University of Twente
G. Durandau University of Twente
Alejandro Moya Esteban University of Twente
Ronald C. Van 't Veld University of Twente
A.C. Schouten Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering , University of Twente
Massimo Sartori University of Twente
Research Group
Biomechatronics & Human-Machine Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2019 Christopher P. Cop, Guillaume Durandau, Alejandro Moya Esteban, Ronald C. Van 'T Veld, A.C. Schouten, Massimo Sartori
DOI: https://doi.org/10.1109/EMBC.2019.8857391
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Published Date

2019

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Biomechanical Engineering

Research Group

Biomechatronics & Human-Machine Control

Abstract

Joint stiffness estimation under dynamic conditions still remains a challenge. Current stiffness estimation methods often rely on the external perturbation of the joint. In this study, a novel 'perturbation-free' stiffness estimation method via electromyography (EMG)-driven musculoskeletal modeling was validated for the first time against system identification techniques. EMG signals, motion capture, and dynamic data of the ankle joint were collected in an experimental setup to study the ankle joint stiffness in a controlled way, i.e. at a movement frequency of 0.6 Hz as well as in the presence and absence of external perturbations. The model-based joint stiffness estimates were comparable to system identification techniques. The ability to estimate joint stiffness at any instant of time, with no need to apply joint perturbations, might help to fill the gap of knowledge between the neural and the muscular systems and enable the subsequent development of tailored neurorehabilitation therapies and biomimetic prostheses and orthoses.

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