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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
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Robust step detection from different waist-worn sensor positions – implications for clinical studies

Authors: Tietsch, M.; Mueller, A.;

Robust step detection from different waist-worn sensor positions – implications for clinical studies

Abstract

The dataset contains tri-axial acceleration and gyroscope data (100 Hz sampling) from walks from 19 healthy volunteers, each walking up to three times a parcours of 20 meters with self-selected speed, slow speed or with five soft turns at self-selected speed. Each participant wore 11 time-synchronized sensors during these tests: left/right foot, 5 around waist, non-dominant wrist and upper arm and collar and pocket. In addition to the sensor recordings each 20 meter walk was timed with a stop-watch. Also see: https://doi.org/10.1159/000511611

Parts of this dataset was analysed and published in Digital Biomarkers, special issue "The Future of Digital Health" (Tietsch et al., 2020, https://doi.org/10.1159/000511611).

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Keywords

gait walking accelerometer gyroscope magnetometer sensors wearing-position

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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