Data and software underlying the publication: Foot progression angle estimation using a single foot-worn inertial sensor

DOI:10.4121/67b940cb-d316-43c5-82bd-1cf2494bc677.v1
The DOI displayed 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: 10.4121/67b940cb-d316-43c5-82bd-1cf2494bc677
Datacite citation style:
Wouda, Frank; Peter Veltink; van Beijnum, Bert-Jan; Harlaar, Jaap; Jaspar, Stephan (2023): Data and software underlying the publication: Foot progression angle estimation using a single foot-worn inertial sensor. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/67b940cb-d316-43c5-82bd-1cf2494bc677.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Calculate the foot progression angle according to the methods described in "Foot progression angle estimation using a single foot-worn inertial sensor" https://doi.org/10.1186/s12984-021-00816-4). It requires Movella DOT IMU input (of which example *.csv files are included) to calculate the foot progression angle using footworn IMUs.

History

  • 2023-09-14 first online, published, posted

Publisher

4TU.ResearchData

Format

text/csv files

Funding

  • MiniSens (grant code 13917) STW

Organizations

University of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science
VU University, Department of Rehabilitation Medicine, Amsterdam Movement Sciences
TU Delft, Faculty of Mechanical, Maritime and Materials Engineering (3ME), Department of Biomechanical Engineering

DATA

Files (2)