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
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doi: 10.4121/67b940cb-d316-43c5-82bd-1cf2494bc677
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
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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
associated peer-reviewed publication
Foot progression angle estimation using a single foot-worn inertial sensor
funding
- MiniSens (grant code 13917) STW
organizations
University of Twente, Faculty of Electrical Engineering, Mathematics and Computer ScienceVU 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)
- 544 bytesMD5:
e393428ff13760b4e2a9df8f892668e0
README.MD - 5,600,180 bytesMD5:
00568ec45b1b69d4a5944dbaf414764b
20230912 - FPA.zip -
download all files (zip)
5,600,724 bytes unzipped