A Reference Data Set for the Study of Healthy Subject Gait with Inertial Measurements Units
Cyril Voisard, Nicolas de l’Escalopier, Albane Moreau, Damien Vienne-Jumeau, Nicolas Ricard, Laurent Oudre
⚠ This is a preprint. It may change before it is accepted for publication.

Abstract

This article provides a comprehensive description of a dataset consisting of 110 multivariate gait signals collected using three inertial measurement units. The data was obtained from a sample of 19 healthy subjects who followed a predefined protocol: standing still, walking 10 meters, turning around, walking back, and stopping. One notable aspect of this dataset is the inclusion of extensive signal metadata, including the start and end timestamps of each footstep, along with contextual information for each trial. Part of this dataset was previously utilized to develop and assess a step-detection algorithm, and as a reference for a multidimensional tool in gait quantification.

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