Time-varying system identification methods for describing human joint impedance

doi: 10.4121/16866376.v1
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
Datacite citation style:
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
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
Delft University of Technology logo
usage stats
120
downloads
490
views
1
citations
time coverage
2018-2021
licence
cc-by.png logo CC BY 4.0
This dataset contains data and scripts used in:
"Quantitative comparison of time-varying system
identification 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.
history
  • 2021-11-09 first online, published, posted
publisher
4TU.ResearchData
format
*.txt; *.m; *.mat; *.slx
funding
  • Dutch Research Council VENI - project number 17351
organizations
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

DATA

files (1)