The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/16866376

van de Ruit, Mark; Schouten, Alfred; Mugge, Winfred; Lataire, John; Cavallo, Gaia et. al. (2021): Time-varying system identification methods for describing human joint impedance. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/16866376.v1

Dataset

• Biomedical Engineering
• Human Movement and Sports Science

human motor control, joint impedance, time-varying system identification

2018-2021

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Mark van de Ruit , Alfred Schouten , Winfred Mugge , John Lataire , Gaia Cavallo , Daniel Ludvig

This dataset contains data and scripts used in:"Quantitative comparison of time-varying systemidentification methods to describe human joint impedance",Annual Reviews in Control, 2021
The data includes simulation and experimental data to identify impedance of the human ankle joints. Five time-varying system identification methods have been used (the ensemble impulse response function, short data segment, basis impulse response function, ensemble spectral and kernel based regression method). For some methods the source files can be found elsewhere.

• 2021-11-09 first online, published, posted

4TU.ResearchData

*.txt; *.m; *.mat; *.slx

Quantitative comparison of time-varying system identification methods to describe human joint impedance

• Dutch Research Council VENI - project number 17351

TU Delft, Faculty of Mechanical, Maritime and Materials Engineering (3mE), Department of Biomechanical Engineering
Vrije Universiteit Brussel, Department of ELEC
Northwestern University, Department of Biomedical Engineering