- published
- 2019-11-16
- reference
- Charles Truong, Rémi Barrois-Müller, Thomas Moreau, Clément Provost, Aliénor Vienne-Jumeau, Albane Moreau, Pierre-Paul Vidal, Nicolas Vayatis, Stéphane Buffat, Alain Yelnik, Damien Ricard, and Laurent Oudre, A Data Set for the Study of Human Locomotion with Inertial Measurements Units, Image Processing On Line, 9 (2019), pp. 381–390. https://doi.org/10.5201/ipol.2019.265
Communicated by Luis Álvarez
Abstract
This article thoroughly describes a data set of 1020 multivariate gait signals collected with two inertial measurement units, from 230 subjects undergoing a fixed protocol: standing still, walking 10 m, turning around, walking back and stopping. In total, 8.5~h of gait time series are distributed. The measured population was composed of healthy subjects as well as patients with neurological or orthopedic disorders. An outstanding feature of this data set is the amount of signal metadata that are provided. In particular, the start and end time stamps of more than 40,000 footsteps are available, as well as a number of contextual information about each trial. This exact data set was used in [Oudre et al., Template-based step detection with inertial measurement units, Sensors 18, 2018] to design and evaluate a step detection procedure.
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- full text manuscript: PDF (1.4MB)
- Dataset: GaitData.zip
History
- Note from the editor: the manuscript of the article was modified on 2022-01-01 to include information about its editors. The original version of the manuscript is available here.