Dataset underlying the research on physical fatigue detection in running using inertial measurement units (IMUs)

doi:10.4121/14307743.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: 10.4121/14307743
Datacite citation style:
Marotta, Luca (2021): Dataset underlying the research on physical fatigue detection in running using inertial measurement units (IMUs). Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/14307743.v1
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Dataset
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This dataset contains data collected during fatigue detection experiments in running using IMUs.Subjects underwent a fatiguing protocol consisting of three distinct consecutive runs on an athletic track:1. The first run consisted of a 4000 m run (10 laps) at a constant speed, determined as 100% of the average speed of the subject during the best performance in the previous year on a 5 to 10 km race;2. The second run was performed according to a fatiguing protocol. The speed in this fatiguing protocol started at the same level of the first run and increased progres-sively of by 0.2km/h every 100 m. Perceived fatigue was assessed by means of a Borg Rating of Perceived Extertion (RPE) Scale (min-max score 6-20) [20], asked to the runner every 100 m. The fatiguing protocol was terminated once the RPE was higher than 16 (RPE between hard and very hard) , or, if such requirement was not met, after 1200m;3. The third run consisted of a 1200m run (3 laps), in which speed was kept constant and equal to the first 4000 m run.

pXXX_XXX_0-2K: contains the Segment and Joint data exported from MVN for the first half of the first runpXXX_XXX_2-4K: contains the Segment and Joint data exported from MVN for the second half of the first runpXXX_XXX_postfatigue1200m: : contains the Segment and Joint data exported from MVN for the third run
pXXX_strides: contains the segmented strides from each subject

TableFeats: contains values used for the machine learning pipeline, after normalization over each single subject
history
  • 2021-03-29 first online, published, posted
publisher
4TU.ResearchData
organizations
University of Twente;
Roessingh Research and Development

DATA

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